Well-Known Facts – facts that are known to a wide range of people, including judges. That is why they do not need to be proven. Even Roman jurists recognized the axiomatic rule: “What is generally known cannot be proven.”
A variety of facts can be generally known: for example, about natural disasters, city buildings (for example, the height of a bridge over a river), wars, revolutions, distances between certain streets, towns, etc. This group of facts is characterized by their locality - what all residents of a particular city know, the judges of the capital may not know. Over time, the memory of certain events, actions, movements that somehow influence people’s lives is erased, and what was generally known 10–25 years ago is now known to a relatively small circle of people.
There is a group of well-known facts, the knowledge of which is not characterized by locality. These are the physical, chemical, mechanical, technological properties of things and objects, etc., for example: the fabric of clothing is usually easy to tear; the TV will most likely break from a sharp impact; synthetic detergents are toxic, etc.
Facts that were previously called notorial are close to well-known facts. They are easily established from written sources, the reliability of which is usually not disputed by anyone. For example, what day of the week was October 5, 1997, what was the air temperature on this or that day, etc.
The characteristics of specific people cannot be considered generally known, since these are not facts, but subjective judgments.
fff2
See also:
Noise immunity– the ability of a device (system) to receive information without interference with a given degree of reliability, i.e. perform its functions in the presence of interference.
Noise immunity is assessed by the intensity of interference at which the disruption of the device’s functions does not yet exceed permissible limits. The stronger the interference under which the device remains operational, the higher its noise immunity.
Noise immunity– the ability of a device (system) to prevent interference.
According to noise immunity and noise immunity, codes are divided into:
Error detection codes
Correction codes
Anti-interference
Noise-resistant
Noise-proof – codes in which the message can be correctly identified (noise immunity + transmission secrecy).
7.Characteristics of codes: number systems, power, relative speed, weight.
base of the number system:
Binary k=2;
Ternary k=3;
Quaternary k=4;
Modulation - physical structure
Coding - mathematical structure
Ternary - in transmission systems, octal - for computers
Word length n (number of digits)
n=k+m, k – information system of symbols, m – test symbols
.Code power– the number of working combinations is determined by the length of the word, the working code Mp; Mp =, Mmax=, k-base of calculus.
Relative code transmission rate.,
Code weight ω– number of units in a binary code combination
10011 -> w=3, 0001 -> w=1.
8. The concept of code redundancy, code distance, characteristic of code distance. Properties of codes depending on the value of the code distance.
Code redundancy - shows which part of the working combinations is used as a working one
= (for binary codes) = 
Code distance d(Hamming distance) – the number of digits in which one combination differs from another. 1≤ d ≤ n
Code transition. The form of the code transition relates the code distance to the correction ability. d = r+s+1 – code transition formula, r – number of detected errors, s – number of corrected errors, r≥s Code transition – number of bits in which one combination differs from another: 
Code properties determined by the minimum code distance.
Properties of codes according to codesdistance
If d=1, then (r=0;s=0) is an equally accessible code
If d=2, then (r=1;s=0)
If d=3, then (r=1;s=1) (r=2;s=0)
If d=4, then (r=3;s=0) (r=2;s=1)
9. Probabilistic characteristics of the code.
To assess the probability of information passing through the CS, probabilistic characteristics are used: Posh or Ppr - these values make up the complete group. Therefore Posh+Rpr=1 (probability of correct passage+probability of error=1)
Law of interference distribution
Signal parameters
MINISTRY OF EDUCATION AND SCIENCE OF THE RUSSIAN FEDERATION
Federal State Budgetary Educational Institution
higher professional education
"KUBAN STATE UNIVERSITY"
(FSBEI HPE "KubSU")
Physics and Technology Faculty
Department of Optoelectronics
COURSE WORK
Research of methods of noise immunity of radio engineering systems
I've done the work
Andriyash Maxim Vladimirovich
Specialty 210302 - Radio engineering
Scientific director
Associate Professor, Ph.D.
A.N. Kazakov
Krasnodar 2013
ABSTRACT
Andriyash M.V. RESEARCH OF INTERFERENCE IMMUNITY METHODS OF RADIO ENGINEERING SYSTEMS. Course work: 29 p. 1 figure, 4 sources.
INTERFERENCE IMMUNITY, INTERFERENCE IMMUNITY OF SYSTEMS, STEALTH OF SYSTEMS.
The purpose of this course work is to improve the educational and methodological complex of the radio engineering systems discipline, which includes: justifying the need to use and improve noise-immune radio systems, analyze the main characteristics and parameters of noise-immune radio systems, the main methods for increasing the secrecy of radio systems, the main methods for increasing the resistance of radio systems to intentional attacks. interference.
The main results of the course work are as follows: in the course of the course work, a justification was carried out for the need to use and improve noise-resistant radio systems, an analysis of the main characteristics and parameters of noise-protected radio systems was made, an analysis of the main methods for increasing the secrecy of radio systems was carried out, and an analysis of the main methods for increasing the resistance of radio systems to intentional interference was carried out. .
Introduction
1. Noise immunity
2. General information about anti-interference methods
2.1 General characteristics of noise immunity
2.2 Relationship between the efficiency of the radio system and its immunity to interference
2.3 Interference immunity of systems
2.4 Stealth of systems
2.5 General characteristics of noise immunity
4. Interference immunity of SRS
4.1 General characteristics of noise immunity of radio communication systems with frequency hopping
Conclusion
noise immunity radio engineering secrecy
Introduction
The problem of increasing the noise immunity of control and communication systems is very acute and has not yet found its solution in most applied problems. The solution to this problem is facilitated by the integrated use of various methods and means (signals of complex shapes, optimal methods for processing them, phased antenna arrays, high-speed digital technology, modern technology, organizational measures).
The most important way to achieve the required noise immunity of radio communication systems (RCS) when exposed to organized (intentional) interference is the use of signals with pseudo-random frequency hopping (PRFC) and the use of optimal and quasi-optimal algorithms for processing such signals.
However, the problem of the effectiveness of SRS with PPFR, research and development of promising methods for increasing the noise immunity of SRS, especially in the context of constant improvement of tactics and technology of electronic suppression (ERS), remain relevant and important from both a scientific and practical point of view. The possibilities that have recently emerged for the widespread introduction of high-speed microprocessor technology and modern element base into SRS make it possible to implement new principles for the formation, reception and processing of signals from frequency hopping, including frequency diversity of symbols with high multiplicity and short duration of elements, the joint use of M-ary frequency shift keying ( FM) and noise-resistant coding of signals from frequency hoppers and adaptive antenna arrays. All this makes it possible to ensure high noise immunity of the SRS when exposed to various types of organized interference. 1. Noise immunity The ability of a radio engineering system (RTS) to function with a given quality in conditions of electronic countermeasures (ECM) is called its noise immunity. Noise immunity can be characterized by the following probability indicator: (1)
Where, Ppd - probability of suppression of RTS, characterizes the secrecy of the system; pu0 is the probability (noise immunity) of the RTS successfully completing its task in the absence of the RTS; pu1 is the probability of successfully completing the RTS task under REP conditions. In turn, it is proposed to determine the probability Ppd in the form: (2)
Where, Ррз is the probability that the parameters of the signals used in the RTS will be determined (explored) by the enemy's electronic warfare system; Risp - the probability of the enemy using electronic warfare equipment, provided that the parameters of the signals are explored with the accuracy necessary to organize suppression; Rpp is the probability of the effect of electronic jamming interference on the receiver of the RTS under consideration, provided that the signal parameters are explored (estimated) with a given accuracy and electronic jamming means are used. Throughput With single-channel or multi-channel, but with homogeneous RTS channels, is usually measured in bits per second. For heterogeneous channels during digital processing, this indicator is also measured in the same units. So the throughput (3)
At E ETP, Where, J is the amount of information retrieved during time T, e - accuracy indicator, edop - its permissible value. 2. General information about anti-interference methods Any radio engineering system can be significantly affected by the influence of various types of interference, methods of protection against which are based on the use of differences in signals and interference. These differences allow for the primary selection of signals: frequency, time, spatial and polarization. When the spectra of the signal and noise overlap, noise suppression is possible in processing devices that take into account differences in the fine structure of the signal. Possible differences between signal and interference, which are used to suppress the effect of interference, are as follows. If the spectra of the signal and interference differ, filtering circuits are used to combat the interference. The following situations are possible: − spectra of interference and signal do not overlap, − the interference spectrum is concentrated in a section of the signal spectrum, − the spectra of the noise and signal overlap, but there are differences in their fine structure. When the spectra of interference and signal overlap, when frequency tuning or rejection is ineffective, comb or matched filters are used. Differences in the structure of the signal and interference spectra are also used in moving target selection devices (MTS) against the background of passive interference. The principles of SDC will be discussed below. Differences in the temporal structure of signals and interference are used to combat pulsed interference that has parameters that differ from the signal: duration, repetition period, time of arrival. The use of signal coding by the number of pulses and the interval between them, selection by duration during automatic target tracking - these are some of the existing methods of combating these types of interference. Differences in the spatial position of signal sources and interference make it possible to significantly reduce the effect of interference by increasing the resolution of the radar and RNS in angular coordinates, suppressing the side lobes of the pattern, and compensating for interference falling along the side lobes of the pattern. Differences in the polarization structure of signals and interference are currently used to suppress interfering reflections from hydrometeors through the use of polarized antennas. 1 General characteristics of noise immunity The noise immunity of a radio system characterizes its ability to maintain a given accuracy of information retrieval and throughput in the presence of interference. The noise immunity of the RTS is ensured by the noise immunity and secrecy of its action. For scientific RTS for information extraction, system secrecy is not mandatory and therefore the concept of noise immunity coincides with the concept of noise immunity. The throughput of the RTS for information retrieval is determined by the maximum speed of information retrieval with a given accuracy Throughput With single-channel or multi-channel, but with homogeneous RTS channels, is usually measured in bits per second. For heterogeneous channels during digital processing, this indicator is also measured in the same units. Thus, throughput C = max(Jr) at e ETP, where J is the amount of information retrieved during time T, e is an accuracy indicator, EDP is its permissible value. The maximum theoretically achievable throughput C is called potential. It depends on the data taken in its determination. In the absence of noise for discrete messages, information theory where Vk is the average speed of the k-th signal, n is the number of types of transmitted symbols. In the presence of interference in the form of normal white noise, Shannon’s formula is valid Obviously, the throughput of C ceases to depend on DD. In information retrieval systems, perfect encoding of source messages is impossible. The resolution of the RTS is the ability of the system to maintain a given accuracy of information extraction under the interfering influence of adjacent signals (coming from adjacent ranges, with close Doppler shifts, etc.). This indicator is completely determined by the resolution of the signals. 2 Relationship between the efficiency of the radio system and its immunity to interference Radio control and communication systems, as a rule, are an integral part of complex control systems (objects, people) and are intended for assessing and transmitting measurement information characterizing the state vector of controlled objects, for transmitting command and various types of connected information. The ability of a control complex to perform a task under given conditions is usually characterized by its effectiveness. Naturally, for radio control and communication systems that are part of such a complex, it is advisable to introduce the concept of efficiency, which should be understood as the ability to perform a task (particular, in relation to the complex as a whole) under given conditions. The effectiveness of control and communication systems depends on a number of factors, such as accuracy, survivability, reliability, noise immunity, and fidelity of information transmission. In different control and communication systems, as well as at different stages of their operation, the importance of the listed factors may be different. Thus, in control systems for moving objects, the factor of accuracy in estimating motion parameters or accuracy of estimating the state vector of an object usually comes to the fore. If such an assessment is carried out under conditions of radio countermeasures, then the factor of noise immunity or noise immunity of the radio system becomes of great importance. In this case, the required accuracy of estimating the object’s state vector must be achieved in a complex noise environment, which will largely be determined by the noise immunity of the control system. Accuracy characteristics also turn out to be very important in communication systems. Thus, the accuracy of the received information depends on the accuracy of synchronization in digital communication systems. In this case, accuracy and noise immunity are often closely related. Modern radio control systems are complex multifunctional (combined) systems in which the same signal can be used both to measure motion parameters and to synchronize and transmit command (communication) information. It is obvious that in such systems the relationship between accuracy and noise immunity becomes even closer. 3 Interference immunity of systems By noise immunity of a control and communication system we mean its ability to perform tasks under conditions of electronic jamming (ERS). Thus, noise immunity is that component of system efficiency that is characterized by the ability to withstand electronic electronic control measures. Therefore, the quantitative noise immunity criterion must be consistent with the efficiency criterion. Since the probability of its completion is taken as an efficiency criterion as a measure of the success of completing a given task, then, as a criterion for noise immunity, it is advisable to take the probability of the system performing a given task (for example, a given fidelity of information transmission or accuracy) under electronic electronic transmission conditions; In general, electronic warfare includes two successive stages - electronic reconnaissance and radio countermeasures. The purpose of electronic reconnaissance is to establish the fact of operation (radiation) of a radio-electronic system (RES) and determine its parameters necessary for organizing radio countermeasures. The purpose of radio countermeasures is to create conditions that would complicate the operation of the radio electronics system or even lead to the failure of the task. The main method of radio countermeasures is jamming. Jamming will be more effective the more information about the suppressed electronic zone is identified at the stage of radio reconnaissance and used in organizing radio countermeasures. Thus, the noise immunity of RES will depend on the technical characteristics of RES, on the relative position of RES and reconnaissance and suppression equipment, on the tactics of using RES, on operating time, etc. The combination of these characteristics and conditions is random, so noise immunity should be considered for some strictly defined conditions. If we designate - the probability of reconnaissance of the RES parameters necessary for organizing radio countermeasures, and - the probability of disruption of the RES operation as a result of radio countermeasures, then the noise immunity criterion can be represented in the following form: . Probability quantitatively reflects the property of RES, which can be called secrecy. By secrecy we mean the ability of a radio electronic system to withstand radio reconnaissance measures aimed at detecting the fact of operation of a radio electronic zone and determining the signal parameters necessary for radio countermeasures. Accordingly, the value can be taken as a criterion for secrecy. Probability depends on the ability of the RES to perform a task under the influence of interference. Therefore the value can be accepted as a noise immunity criterion. This criterion determines the probability of the system completing a task under radio jamming conditions. Thus, the noise immunity of RES is determined by its secrecy and noise immunity. Let's consider individual noise immunity indicators. 4 Stealth of systems Electronic reconnaissance, as a rule, involves the sequential implementation of three main tasks: detecting the fact of the operation of electronic electronic devices (signal detection), determining the structure of the detected signal (based on determining a number of its parameters) and disclosing the information contained (transmitted) in the signal. The last task sometimes has independent significance (it is one of the final goals). In general, revealing the meaning of the transmitted information makes it possible to organize more effective electronic communication. The listed tasks of electronic intelligence can be contrasted with three types of signal secrecy: energy, structural and information. Energy secrecy characterizes the ability to withstand measures aimed at detecting a signal by a reconnaissance receiving device. As is known, signal detection occurs in conditions when the reconnaissance receiver is subject to interference (noise), and can be accompanied by two types of errors: omission of a signal when it is present at the input and false detection (false alarm) when there is no signal. These errors are probabilistic in nature. A quantitative measure of energy secrecy can be the probability of correct detection (for a given probability of a false alarm RLT), which in turn depend on the signal-to-interference ratio in the radio link under consideration and the decision rules for signal detection. Structural secrecy characterizes the ability to withstand electronic intelligence measures aimed at disclosing a signal. This means recognizing the shape of a signal determined by the methods of its encoding and modulation, i.e. identifying the detected signal with one of many a priori known signals. Consequently, to increase structural secrecy it is necessary to have the largest possible ensemble of signals used and to change the shape of the signals quite often. The task of determining the signal structure is also statistical, and a quantitative measure of structural secrecy can be the probability of disclosing the signal structure provided that the signal is detected. Thus, is a conditional probability. Information secrecy is determined by the ability to resist measures aimed at revealing the meaning of information transmitted through signals. Revealing the meaning of transmitted information means identifying each received signal or their combination with the message that is being transmitted. This problem is solved by identifying a number of characteristics of a signal, for example, the place of a given signal in the set of received ones, the frequency of its occurrence, the connection between the factors of the appearance of a particular signal and a change in the state of the controlled object, etc. The presence of a priori and a posteriori uncertainties makes this problem probabilistic, and in As a quantitative measure of information secrecy, the probability of revealing the meaning of the transmitted information is taken provided that the signal is detected and isolated (i.e. its structure is revealed). Hence, is also a conditional probability. Stealth is determined by the probability of reconnaissance of the RES signal , That's why . Often the task of revealing the meaning of the transmitted information is not set, and then one can accept And . In some cases, to organize radio countermeasures, it is enough to detect the signal of the suppressed RES. Wherein identified with . Energy and structural secrecy are the most important characteristics of the signal and radio electronics, which are faced by both radio equipment design engineers and engineers operating it. Therefore, these types of secrecy will be given the main attention in the future. 5 Noise immunity The noise immunity of a radio electronic network is understood as the ability to perform a task under the influence of interference created during the organization of a radio electric power plant. Thus, noise immunity is the ability of RES to resist the harmful effects of interference. Often, noise immunity analysis is carried out regardless of the reason for the appearance of noise at the input of the RES. Since noise immunity depends on a number of random reasons, its quantitative measure can be the probability disruption of the functioning of the electronic distribution system (failure to complete a given task) when exposed to interference. Probability can be defined as probability! that the actual value of the signal-to-noise ratio (at the output of the RES receiver will become less than a certain critical (for a given type of interference), in which the functioning of the RES is disrupted, i.e. ). The noise immunity of RES depends on a combination of a large number of factors - the type (form) of interference, its intensity, the shape of the useful signal, the structure of the receiver, the antenna, the methods used to combat interference, etc. These factors determine the directions for research into noise immunity, which will be partially considered in the future . Here we will dwell on the energy noise immunity of reception, which is determined by the energy characteristics of the signal and interference, assuming that they differ in shape and that the receiver matches the signal with fluctuation interference. This agreement takes place in real conditions and does not violate the generality of the analysis. Such consideration makes it possible to identify a number of useful patterns, as well as set requirements for RES signals that provide increased noise immunity. First, we will consider the noise immunity of the complex signal receiver itself, and then the noise immunity of the RES. It is known that the maximum ratio of signal to white noise at the output of the optimal receiver does not depend on the signal shape and is equal to Consequently, if the signal is isolated against the background of only the internal noise of the receiver, then the noise immunity of receivers matched to signals of any shape will be the same. If the interference is created by an external source of interference, then it is convenient to represent q as the ratio of the signal and interference powers. If the interference has a uniform spectral density in the signal band F, then for a signal with duration T we can write (4)
Where, .
Let us show that formula (1.20) will also be valid under the action of narrowband interference with a power . Thus, if we imagine the optimal receiver in the form of a correlator, then at the output of the correlator multiplier the spectrum of this interference will expand to the value of the signal band F, and only part of the interference spectrum will pass through the integrator with the integration limit T. As a result, the power of the interference and signal at the correlator output will be respectively equal to , and the signal-to-interference ratio is determined from (1.20). From formula (1.20) it follows that the larger the signal base, the greater the interference power required to suppress the receiver for given values of q, .
It is easy to show that the noise immunity of a complex signal receiver with respect to pulsed noise of duration will be determined Obviously, when a mixture of broadband and narrowband interference with powers is applied to the receiver input And , That 3. Justification of the need to use and improve noise-protected RTS The intensive development of means of information transmission (radio communications, telemetry, radar, etc.) has led to a significant saturation of the airwaves with electromagnetic radiation. Moreover, the situation is complicated by the fact that in a limited space, tens and hundreds of electronic devices can simultaneously operate in continuous and pulsed radiation, with simple and complex signals, for reception and transmission. Thus, on an ocean-going ship used as a tracking, communication and control point for a spacecraft, there is: HF and VHF radio communications equipment; system for determining ship coordinates; unified time system; system for receiving data on satellite coordinates; medical monitoring system for astronauts; satellite tracking system using radar (Rizl=1 MW, f Î 5,4¸ 5.8 Hz); command control system (Rizl=10 kW, f Î 400¸ 500 MHz); telemetry data reception system (Ppr = -127 dB/V, f Î 105¸ 140 MHz, 210 ¸ 200 MHz; 2.2 ¸ 2.3 GHz); HF and UHF radio communication system for real-time transmission of telemetry data received from a satellite, etc. The tightness on the air is increased not only by the quantitative growth of radio-electronic technology, but also by some of its qualitative changes. The high level of sensitivity (up to 10-22 W) and wide bandwidth of many modern radio control units makes them very susceptible to radio interference. This applies, for example, to receiving equipment with low-noise PUs, TWTs and TDs, in the development of which the main attention is paid to increasing sensitivity. Such equipment is susceptible not only to regular emissions from transmitters, but also to chaotic broadband interference generated by various switches, communication devices, ignition systems, etc. The creation of ultra-powerful pulse transmitters (for example, MCR) has led to an increase in emissions at the second, third and subsequent harmonics of the fundamental frequency. It should be noted that a significant number of RES operate simultaneously in the same frequency range. From this it can be seen that in modern conditions the input of radio receiving devices (RPUs) is very likely to receive interference from nearby RES, and this interference can have a very high level. Despite this, the focus of radio equipment designers is often on obtaining the highest possible signal-to-noise ratio. Here it is necessary to dwell on the criterion of feasibility, i.e. In such a complex interference situation as described above, it may not be advisable to achieve a very high signal-to-noise ratio. It is advisable, at a certain (satisfactory for practice) signal-to-noise ratio, to strive to obtain the best compatibility characteristics of electronic devices. Thus, one of the problems that arises during the creation and operation of REA is ensuring the electromagnetic compatibility of REA (EMC REA). This name also refers to the set of properties of RES and their operating conditions under which normal operation of RES is possible (i.e., maintaining their certain quality characteristics). This problem covers a wide area of radio electronics and includes: mathematical model - analysis of interference situations and the passage of signals (mutual interference) through standard RES; synthesis of signals from radio control units, transmitters and antenna devices that provide EMC for electronic distribution systems; organization of the work of the RES, ensuring minimal influence of the RES on each other (frequency, time and polarization regulation, etc.); development of standardization and methods for measuring EMC parameters. 4. Interference immunity of SRS Radio control and communication systems, as a rule, are an integral part of complex control systems (objects, people) and are intended for transmitting measurement information characterizing the state vector of controlled objects, transmitting command and various types of connected information. At the same time, the required accuracy of message transmission, as well as the performance of other functions, must be achieved in a complex noise environment, which will largely be determined by the noise immunity of the communication channel. In connection with the complex crime situation and the terrorist threat, the resistance of the communication channel to the action of intentional interference created by third parties for the purpose of distorting, suspending or stopping the transmission of information is important. Objects of critical importance (for example, main product pipelines) that use open communication channels to monitor technical condition require special attention. As a rule, for such objects the nature and structure of the information transmitted over the communication channel (signals from sensors, control commands for individual devices) is known. Messages are usually transmitted periodically and in batches. Third parties, using electronic intelligence equipment, can accumulate information about the communication mode, frequency ranges used, types of signals, modulation, etc. for a long time. This information can be used both to formulate a mode of counteraction to the communication system as a whole, and specific intentional interference to the channel. Therefore, to increase noise immunity, there is a need to timely detect the presence of intentional interference in the received signal and adapt the communication channel to the effect of interference. As is known, the noise immunity of radio communications (RCF) is achieved through a set of organizational measures, methods and means aimed at ensuring stable operation of the CRC under the influence of organized (deliberate) interference from electronic jamming (REC). The process of functioning of the SRS in conditions of organized interference, in its physical essence, can be represented as an electronic conflict, in which, on the one hand, the SRS participates, and on the other, the electronic electronic control system, consisting in the general case of a radio reconnaissance station (RTR) and the jamming station itself. Figure 1 generally shows the structural diagram of an electronic conflict. A channel is considered secure if it provides the required information transmission secrecy and resistance to intentional interference. The model of a secure communication channel (SCC) must additionally contain a model of a specially designed transmitted signal, a model of intentional interference, and methods for combating interference. 1 General characteristics of noise immunity of radio communication systems with frequency hopping Noise immunity of radio communication systems with frequency converters It is known that noise immunity and secrecy are the two most important components of SRS noise immunity. In this case, in the general case, the noise immunity of SRS with frequency frequency control (as well as any other SRS) is understood as the ability to function normally, performing tasks of transmitting and receiving information in conditions of radio interference. Consequently, the noise immunity of SRS is the ability to withstand the harmful effects of various types of radio interference, including, first of all, organized interference. The strategy for combating organized interference of SRS with PDFR consists, as a rule, in “escape” of SRS signals from the influence of interference, and not in “confrontation” with them, as is implemented in SRS with FM1IPS. Therefore, in SRS with frequency frequency control, when protecting against interference, an important characteristic is the actual operating time at one frequency. The shorter this time, the higher the likelihood that SRS signals with frequency converters will not be affected by organized interference. The noise immunity of an SRS with frequency frequency control depends not only on the operating time at one frequency, but also on other important parameters of the interference station (SP) and the SRS, for example, on the type of interference and its power, the power of the useful signal, the structure of the receiving device and the noise immunity methods incorporated in the SRS . The effective impact of interference on the SRS with frequency frequency control can be achieved only if the jammer knows the relevant parameters of the SRS signals, for example, the center frequencies of the channels, the speed of frequency jumps, the width of the information frequency band, signal power and interference at the location of the SRS receiving device. The jammer obtains the specified SRS parameters, as a rule, directly with the help of a radio reconnaissance station (RTR), as well as by recalculating the measured SRS parameters into other SRS characteristics that are functionally related to them. For example, by measuring the duration of a frequency hop, you can calculate the bandwidth of the frequency channel of the CPC receiver. In general, RTR, by receiving and analyzing intercepted signals not only from SRS, but also from other radio electronic means (RES), ensures the collection of information about the opposing party as a whole. SRS and RES signals contain many technical characteristics that are intelligence information. These characteristics determine the “electronic signature” of the SRS and RES and allow us to establish their capabilities, purpose and affiliation. A generalized algorithm for collecting radio intelligence data on signal parameters and SRS characteristics is shown in Fig. 1 Figure 1 - Generalized algorithm for collecting radio intelligence data on signal parameters and SRS characteristics To assess the noise immunity of the SRS under conditions of exposure to various types of interference, it is necessary to have appropriate indicators. Given the selected signal models, the internal noise of the receiving device and additive noise in discrete message transmission systems, the preferred indicator of a quantitative measure of noise immunity is the average error probability (AEP) per bit of information. Other indicators of noise immunity of the SRS, for example, the required signal-to-interference ratio at which the specified quality of information reception is ensured, the probability of an error in the code word, and others, can be expressed in terms of SVO per bit. Minimization of the SVO per bit under the condition of equally probable transmission of symbols can be achieved through the use of an algorithm that implements the maximum likelihood rule , (6)
which for binary SRS has the form: , (7)
where is the likelihood ratio for -th signal. In the further presentation, most attention will be focused on the development and analysis of algorithms for calculating the SVO per bit of information. The analysis of SVO per bit will be carried out under the influence of Gaussian noise of the SRS receiving device and additive organized interference, mainly in relation to canonical (typical) FM systems, which are the basic basis for more complex SRS. Conclusion The main results of the course work are as follows: A justification was made for the need to use and improve noise-protected RTS. An analysis was made of the main characteristics and parameters of noise-protected RTS. An analysis of the main methods for increasing the stealth of RTS was carried out. An analysis of the main methods for increasing the resistance of radio systems to intentional interference was carried out. List of sources used Information technologies in radio systems: textbook / V.A. Vasin, I.B. Vlasov, Yu.M. Egorov et al., Ed. I.B. Fedorova. -m.: publishing house of MSTU named after N.E. Bauman, 2004.-672s Radio engineering systems: Textbook for universities on special topics. Radio engineering . Edited by Yu.P. Kazarinov. - M.: Higher School, 2005. Gonorovsky I.S. Radio engineering circuits and signals. -M.: Radio and communication, 1986.-512 p. Fundamentals of radio engineering systems: textbook / Yu.T.Zyryanov, O.A.Belousov, P.A.Fedyunin. - Tambov: Publishing house of the Federal State Budgetary Educational Institution of Higher Professional Education TSTU, 2011. - 144 p.
Understanding Broadband Signals
1.1 Definition of ShPS. Application of ShPS in communication systems
Wideband (complex, noise-like) signals (WPS) are those signals for which the product of the active spectrum width F and duration T is much greater than unity. This product is called the signal base B. For the ShPS
B = FT>>1 (1)
Wideband signals are sometimes called complex signals in contrast to simple signals (for example, rectangular, triangular, etc.) with B = 1. Since signals with a limited duration have an unlimited spectrum, various methods and techniques are used to determine the width of the spectrum.
Increasing the base in ShPS is achieved by additional modulation (or manipulation) in frequency or phase during the signal duration. As a result, the spectrum of the signal F (while maintaining its duration T) is significantly expanded. Additional intra-signal modulation by amplitude rarely used.
In communication systems with broadband networks, the spectrum width of the emitted signal F is always much greater than the spectrum width of the information message.
ShPS are used in broadband communication systems (BCS) because:
· allow you to fully realize the benefits of optimal signal processing methods;
· provide high noise immunity of communication;
· allow you to successfully combat multipath propagation of radio waves by splitting the beams;
· allow simultaneous operation of many subscribers in a common frequency band;
· allow you to create communication systems with increased secrecy;
· ensure electromagnetic compatibility (EMC) of the ShPSS with narrowband radio communication and radio broadcasting systems, television broadcasting systems;
· provide better use of the frequency spectrum in a limited area compared to narrowband communication systems.
Noise immunity of ShPSS
It is determined by the well-known relation connecting the signal-to-noise ratio at the receiver output q 2 with the signal-to-noise ratio at the receiver input ρ 2:
q 2 = 2Вρ 2 (2)
where ρ 2 = R s / R p (R s, R p - ShPS power and interference);
q 2 = 2E/ N p, E - energy of the ShPS, N p - spectral power density of the interference in the band of the ShPS. Accordingly, E = P with T , a N p = P p / F;
B - ShPS base.
The signal-to-noise ratio at the output q 2 determines the operating characteristics of the NPS reception, and the signal-to-noise ratio at the input ρ 2 determines the energy of the signal and noise. The value of q 2 can be obtained according to the system requirements (10...30 dB) even if ρ 2<<1. Для этого достаточно выбрать ШПС с необходимой базой В, satisfying (2). As can be seen from relation (2), reception of NPS by a matched filter or correlator is accompanied by a signal amplification (or noise suppression) by 2 times. That is why the value
K ShPS = q 2 /ρ 2 (3)
is called the processing gain of the ShPS or simply the processing gain. From (2), (3) it follows that the processing gain K ShPS = 2V. In SHPS, information reception is characterized by the signal-to-interference ratio h 2 = q 2 /2, i.e.
h 2 = Bρ 2 h (4)
Relations (2), (4) are fundamental in the theory of communication systems with broadband networks. They were obtained for interference in the form of white noise with a uniform power spectral density within a frequency band whose width is equal to the width of the NPS spectrum. At the same time, these relationships are valid for a wide range of interference (narrowband, pulsed, structural), which determines their fundamental significance.
Thus, one of the main purposes of communication systems with broadband networks is to ensure reliable reception of information under the influence of powerful interference, when the signal-to-interference ratio at the receiver input ρ 2 can be much less than unity. It should be noted once again that the above relations are strictly valid for interference in the form of a Gaussian random process with a uniform spectral power density (“white” noise).
Main types of ShPS
A large number of different SPS are known, the properties of which are reflected in many books and journal articles. ShPS are divided into the following types:
· frequency-modulated (FM) signals;
· multi-frequency (MF) signals;
· phase-shift keyed (PM) signals (signals with code phase modulation - QPSK signals);
· discrete frequency (DF) signals (signals with code frequency modulation - FFM signals, frequency-shift keyed (FM) signals);
· discrete composite frequency (DCF) (composite signals with code frequency modulation - SKFM signals).
Frequency modulated (FM) signals are continuous signals, the frequency of which varies according to a given law. Figure 1a shows an FM signal, the frequency of which varies according to a V-shaped law from f 0 -F/2 to f 0 +F/2, where f 0 is the central carrier frequency of the signal, F is the spectrum width, in turn equal to the deviation frequency F = ∆f d. The duration of the signal is T.
Figure 1b shows the time-frequency (f, t) plane, on which the shading approximately depicts the energy distribution of the FM signal in frequency and time.
The base of the FM signal by definition (1) is equal to:
B = FT=∆f d T (5)
Frequency-modulated signals are widely used in radar systems because a matched filter can be created for a specific FM signal using surface acoustic wave (SAW) devices. In communication systems, it is necessary to have many signals. At the same time, the need to quickly change signals and switch generation and processing equipment leads to the fact that the law of frequency change becomes discrete. In this case, they move from FM signals to DF signals.
Multi-frequency (MF) signals (Figure 2a) are the sum N harmonics u(t) ... u N (t) , the amplitudes and phases of which are determined in accordance with the laws of signal formation. On the frequency-time plane (Figure 2b), the distribution of the energy of one element (harmonic) of the MF signal at frequency f k is highlighted by shading. All elements (all harmonics) completely cover the selected square with sides F and T. The base of the signal B is equal to the area of the square. The spectrum width of the element is F 0 ≈1/T. Therefore, the base of the MF signal
B = F/F 0 =N (6)
Figure 1 - Frequency-modulated signal and time-frequency plane
i.e., it coincides with the number of harmonics. MF signals are continuous and it is difficult to adapt digital techniques for their formation and processing. In addition to this disadvantage, they also have the following:
a) they have a bad crest factor (see Figure 2a);
b) to obtain a large base IN it is necessary to have a large number of frequency channels N. Therefore, MF signals are not considered further.
Phase-shift keyed (PM) the signals represent a sequence of radio pulses, the phases of which vary according to a given law. Typically, the phase takes two values (0 or π). In this case, the radio frequency FM signal corresponds to a video FM signal (Figure 3a), consisting of positive and negative pulses. If the number of pulses is N , then the duration of one pulse is equal to τ 0 = T/N , and the width of its spectrum is approximately equal to the width of the spectrum of the signal F 0 = 1/τ 0 =N/T. On the time-frequency plane (Figure 3b), the distribution of the energy of one element (pulse) of the FM signal is highlighted by shading. All elements overlap a selected square with sides F and T. FM signal base
B = FT =F/τ 0 =N, (7)
those. B is equal to the number of pulses in the signal.
The possibility of using PM signals as BPS with bases B = 10 4 ...10 6 is limited mainly by processing equipment. When using matched filters in the form of SAW devices, optimal reception of FM signals with maximum bases Vmax = 1000 ... 2000 is possible. FM signals processed by such filters have wide spectra (about 10 ... 20 MHz) and relatively short durations (60 ... 100 µs). Processing of FM signals using video frequency delay lines when transferring the spectrum of signals to the video frequency region makes it possible to obtain bases B = 100 at F≈1 MHz, T ≈ 100 µs.
Matched filters based on charge-coupled devices (CCDs) are very promising. According to published data, using matched CCD filters, it is possible to process FM signals with bases of 10 2 ... 10 3 at signal durations of 10 -4 ... 10 -1 s. A digital correlator on a CCD is capable of processing signals up to a base of 4∙10 4 .
Figure 2 - Multi-frequency signal and time-frequency plane
Figure 3 - Phase-keyed signal and time-frequency plane
It should be noted that it is advisable to process PM signals with large bases using correlators (on an LSI or on a CCD). In this case, B = 4∙10 4 seems to be limiting. But when using correlators, it is necessary first of all to resolve the issue of accelerated entry into synchronism. Since FM signals make it possible to widely use digital methods and techniques of generation and processing, and it is possible to implement such signals with relatively large bases, therefore FM signals are one of the promising types of NPS.
Discrete frequency (DF) the signals represent a sequence of radio pulses (Figure 4a), the carrier frequencies of which vary according to a given law. Let the number of pulses in the DF signal be M , The pulse duration is T 0 =T/M, its spectrum width is F 0 =1/T 0 =M/T. Above each pulse (Figure 4a) its carrier frequency is indicated. On the time-frequency plane (Figure 4b), the squares in which the energy of the DF signal pulses are distributed are shaded.
As can be seen from Figure 4b, the energy of the DF signal is distributed unevenly on the time-frequency plane. HF signal database
B = FT = МF 0 МТ 0 = М 2 F 0 Т 0 = М 2 (8)
since the momentum base is F 0 T 0 = l. From (8) follows the main advantage of DF signals: to obtain the required base Number of channels M = , i.e., significantly less than for MF signals. It was this circumstance that led to attention to such signals and their use in communication systems. At the same time, for large bases B = 10 4 ... 10 6, it is inappropriate to use only DF signals, since the number of frequency channels is M = 10 2 ... 10 3, which seems excessively large.
Discrete Composite Frequency (DCF) The signals are HF signals in which each pulse is replaced by a noise-like signal. Figure 5a shows an FM video signal, individual parts of which are transmitted at different carrier frequencies. Frequency numbers are indicated above the FM signal. Figure 5b shows the time-frequency plane, on which the distribution of the energy of the DFS signal is highlighted by shading. Figure 5b is no different in structure from Figure 4b, but for Figure 5b the area F 0 T 0 = N 0 is equal to the number of PM signal pulses in one frequency element of the DFS signal. DFS signal base
B = FT =M 2 F 0 T 0 = N 0 M 2 (9)
Number of pulses of the total PM signal N=N 0 M
Figure 4 - Discrete frequency signal and time-frequency plane
The DFS signal shown in Figure 5 contains FM signals as elements. Therefore, we will abbreviate this signal as a DFS-FM signal. As elements of the DFS signal, we can take DFS signals. If the base of the DF signal element B = F 0 T 0 = M 0 2 then the base of the entire signal B = M 0 2 M 2
Figure 5 - Discrete composite frequency signal with phase shift keying DFS-FM and time-frequency plane.
Such a signal can be abbreviated as DSCH-FM. The number of frequency channels in a DFS-FM signal is M 0 M. If the DFS signal (see Figure 4) and the DFS-FM signal have equal bases, then they have the same number of frequency channels. Therefore, the DFS-FM signal does not have any special advantages over the DF signal. But the principles of constructing an FM signal can be useful when constructing large systems of FM signals. Thus, the most promising broadband signals for communication systems are FM, DC, and DFS-FM signals.
Many people think that the protection of electrical signals and transmitted information from electromagnetic interference is ensured exclusively by shielded wires, distance from sources of interference, and testing of transmitting and receiving equipment. However, this is not true; there are many ways to increase the noise immunity of a measurement channel or information transmission channel. Often, designers and developers lose sight of important points, which we will discuss below. One of the disadvantages of wired lines is low noise immunity and the possibility of simple unauthorized connection. Let's look at the main common ways to increase noise immunity.
Selecting a transmission medium. Twisted pair. Twisting the wires together reduces the wave impedance of the conductors, and as a result, interference. Twisted pair cable is a fairly noise-resistant cable. The connectors to which the cable is connected also play an important role in protecting against interference, for example, RJ45 for Ethernet architecture or RS connectors with built-in filters. The disadvantages of twisted pair cable include the possibility of simple unauthorized connection to the network. Coaxial cable is more noise-resistant than twisted pair. Reduces its own radiation, but is more expensive and more difficult to install. Cable fiber optic communication channels. Fiber optic cable - requires conversion of an electrical signal into a light one, can be combined with a channel encoder. Extremely high level of noise immunity and absence of radiation at data transfer rates of 3 Gbit/s. The main disadvantages of fiber optic cable are the complexity of its installation, low mechanical strength and sensitivity to airwaves, including ionizing radiation.
Another way is, oddly enough, to reserve communication channels. Very common, for example, at nuclear power plants in the channels of automated process control systems. Here I would also like to remember 2 points: masking of live power line wires from a lightning strike behind a grounded conductor and deterioration or improvement in the quality of reception when moving near a TV or radio antenna. So, laying your cable in a common tray or conduit does not always play a detrimental role; sometimes other lines can disguise yours and take on most of the interference energy.
Interface selection. The unified 4–20 mA signal has been widely used for several decades to transmit analog signals in the creation of automated control systems. The advantage of this standard is the simplicity of its implementation, the possibility of noise-resistant transmission of an analog signal over relatively long distances. This is a clear example of removing the transmission frequency from the characteristic frequencies of the most likely electromagnetic interference. However, it is absolutely clear that it is not effective in modern digital self-propelled guns. In measurement systems, the unified 4-20 mA signal can only be used to transmit the signal from the sensor to the secondary converter. The noise immunity of such a signal ensures a shift from RF interference to direct current and simplicity of circuit solutions when filtering interference. The RS-485 interface is relatively weakly immune to noise. USB is better protected because it is a serial interface. However, due to the weak first protocols and the electrically unsuccessful design of the connector (reminiscent of a microstrip line), it quite often goes astray due to high-frequency interference. Improved encoding quality in USB 3.0 and the move to micro-USB connectors significantly improve its immunity to electromagnetic influences. Ethernet and Internet - from the point of view of measurement systems, the advantages and disadvantages of these interfaces are generally similar to the USB interface. Naturally, when measuring instruments operate in large distributed networks, these interfaces today have virtually no alternative. GPIB or IEEE-488 is the principle of operation of the interface on byte-serial, bit-parallel information exchange and this explains its high noise immunity compared to packet transmission.
Logical noise immunity. At the physical level, there are many techniques for digitizing a signal to increase noise immunity. For example, using a specific voltage instead of a neutral conductor or ground for a logical zero. It’s even better if the levels are shifted: +12V and -5V or +3V and +12V. The software implementation of noise immunity here consists of using feedback to re-interrogate devices when information is distorted and using noise-proof and restorative coding methods.
A few more techniques for increasing noise immunity:
application of differential signal and reception methods;
the use of separate return conductors inside the cable;
grounding of unused or spare conductors;
elimination of different potentials at different points of grounding or common conductors;
increasing signal power and amplitudes;
broadcasting one interface to another, excluding the disadvantages of both;
increasing the potential difference between logic levels;
removal of transmitted frequencies from the characteristic interference spectrum;
selection of trigger trigger methods (by edges, amplitude, increment, frequency, phase, specific sequence, etc.);
synchronization;
use of logical and signal grounds and their shielding;
The list of techniques is perhaps not exhausted by anything other than the resources, knowledge and ingenuity of a particular person or organization.
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