Comprehensive radar signal analysis system based on amplitude information

Abstract

The invention discloses a comprehensive radar signal analysis system based on amplitude information, which comprises a simulator and a classifier, and is characterized in that the simulator generates pulse signals of a plurality of targets according to set input parameters and overlaps the pulse signals so as to output pulse description words for sorting of the classifier, and the set input parameters comprise a set radar scanning mode; and the classifier sorts the pulse description words, performs dimension reduction and clustering on the pulse signals according to instantaneous parameters of the pulse description words, searches for signals conforming to set radar scanning mode characteristics, and outputs pulse signals belonging to the same radiation source. According to the comprehensive radar analysis system provided by the invention, radar signals of a single radiation source can be accurately extracted from intercepted PDWs which are large in quantity, large in range density and serious in overlapping through the classifier. The radar signal simulator can simulate signals emitted by various radiation sources to generate pulse description words in specified distribution, so that the performance of a classifier algorithm can be evaluated conveniently, and the performance bottleneck can be identified.

Description

Technical Field

[0001] The invention belongs to the field of radar analysis and relates to a comprehensive radar signal analysis system based on amplitude information. Background Art

[0002] Radar attack and defense technology is changing with each passing day. New radars are introduced one after another, and radar signal encryption methods are rapidly iterating, prompting radar signal analysis systems to analyze signals in newer and faster modes. Radar electronic reconnaissance systems capture radar radiation source signals in the frequency domain, spatial domain, and other parameter domains, and store the signals quantitatively. Radar signal sorting is to sort out pulses belonging to different radar radiation sources from the intercepted dense radar pulse stream. Figure 1 As shown. Radar signal sorting is one of the core links in radar reconnaissance signals. Only by sorting out each radar pulse sequence from the randomly overlapping signal stream can the signal parameters be measured, analyzed, and identified, and suppressive interference can be applied to the radar threat radiation source or false target echo signals can be constructed to perform various deceptive interference. The technical level of signal sorting has become an important indicator of the advanced level of electronic intelligence reconnaissance, electronic support reconnaissance and threat warning systems.

[0003] However, with the widespread adoption of radars on various equipment and the increase in the density of radiation sources, and the emergence of new radar systems, the various parameters of radar signals change in various patterns. The overall performance is that the number of radiation sources is large, the density is wide, the signal overlap is serious, and the signal modulation is complex. The battlefield electromagnetic environment is becoming more and more complex, and radar radiation source signal sorting faces unprecedented challenges.

[0004] After the radar reconnaissance system receives the pulse signal, the parameter detection and measurement module first measures the main parameters of the pulse, such as Time of Arrival (TOA), Radio Frequency (RF), Pulse Width (PW), Pulse Amplitude (PA) and Direction of Arrival (DOA). The above-mentioned TOA, RF, PW, PA and DOA are the five most typical instantaneous parameters of the pulse description word (PDW), that is, the parameters that can be directly obtained through measurement. In addition to instantaneous parameters, the parameters that can be obtained through multiple measurements or calculations are secondary parameters, the most important representative of which is the pulse repetition interval (PRI).

[0005] The current electronic anti-interference measures in the transmitter link include: frequency agility or frequency diversity can be used in the transmission frequency. The former refers to the radar changing the transmission frequency between pulses or pulse trains, and the latter refers to several radar transmitters working at different frequencies and making comprehensive use of their received signals. These technologies represent an extended spectrum electronic anti-interference method: the transmitted signal will be as wide as possible in the frequency domain to reduce the detectability during enemy reconnaissance, and increase the load of enemy electronic interference to make interference more difficult. Transmit waveform coding: waveform coding includes pulse repetition frequency hopping, staggered coding and pulse-to-pulse coding. All these technologies make deception interference more difficult because the enemy will not be able to know or predict the exact structure of the transmitted waveform.

[0006] At a time when all types of radar signal transmission systems currently use anti-interference measures related to pulse repetition frequency, it is meaningful to use amplitude information as a reference for radar sorting. For mechanically scanned radars, the envelope represents the scanning shape of the radiating antenna. The pulse amplitude can usually be represented by the power density of the radar signal received by the reconnaissance receiver. The pulses of the same radiation source near the same frequency generally have a constant transmission power. When the distance between the reconnaissance receiver and the radiation source is constant, the change in amplitude is mainly caused by the antenna beam modulation, which reflects the scanning law of the antenna. Therefore, the pulse amplitude parameter in the reconnaissance receiver can be used for signal sorting.

[0007] Assume the radar signal power is P t , the maximum gain of the antenna is G t , the distance between the radar and the reconnaissance platform is R, the atmospheric transmission loss of radio waves is L, then the radiation power density S at the reconnaissance receiving antenna is:

[0008]

[0009] In the formula, F t (θ) is the normalized antenna pattern function, and θ is the angle between the line of sight of the reconnaissance equipment at the radar platform and the current direction of the radar antenna.

[0010] Radars have different uses, performances, and carriers, and their radiation pattern functions often vary greatly, and their accurate expressions are often very complicated. To facilitate engineering calculations, some simple functions can be used to approximate them. The functional relationship between the main lobe gain and the angle of the antenna can generally be expressed by the Sinque function:

[0011]

[0012] In the formula, θ 0.5 is the -3dB beamwidth.

[0013] The use of amplitude information provides a new dimension for analyzing signals for signal sorting. The amplitude-sorted signals can be used to determine the PRI law of the target. In the future, it is hoped that a multi-dimensional signal sorting system combining amplitude and PRI can be established to improve the accuracy of the system. Summary of the invention

[0014] In order to overcome the deficiencies of the prior art, the present invention provides a comprehensive radar signal analysis system based on amplitude information.

[0015] In order to achieve the above object, the present invention adopts the following technical solutions:

[0016] A comprehensive radar signal analysis system based on amplitude information includes a simulator and a sorter. The simulator generates pulse signals of multiple targets and overlaps them according to set input parameters to output pulse description words for sorting by the sorter. The set input parameters include setting a radar scanning mode. The sorter sorts the pulse description words, reduces the dimension of the pulse signals and clusters them according to the instantaneous parameters of the pulse description words, searches for signals that meet the characteristics of the set radar scanning mode, and outputs pulse signals belonging to the same radiation source.

[0017] Furthermore, setting the radar scanning mode includes simulating mechanical scanning radar scanning to generate a quadratic function curve, simulating phased array radar scanning to generate a discrete straight line.

[0018] Furthermore, the target pulse signal generation includes: setting input parameters to determine the target appearance time, based on the setting radar scanning mode, setting the target appearance time as the highest point of the quadratic function curve or discrete straight line, extending the highest point to both sides on the time axis, and generating the target pulse amplitude-arrival time signal.

[0019] Furthermore, the pulse amplitude-arrival time signals of multiple targets are added according to the occurrence time of the signals to generate an overlapping curve, and the overlapping curve appears as a single continuous curve with multiple fluctuations on the pulse amplitude-arrival time graph.

[0020] Furthermore, the set input parameters include: the number of target appearances, the probability distribution of target appearance time, the regularity of pulse repetition interval, and the time length of the pulse sequence.

[0021] Furthermore, it also includes intercepting the overlapping curve, determining the pulse-to-pulse modulation mode based on the pulse repetition interval, generating a pulse timestamp, intercepting the overlapping curve according to the pulse timestamp, and generating a pulse description word.

[0022] Furthermore, the inter-pulse modulation mode includes: one of PRI stagger, PRI sliding, PRI jitter, PRI pulse group agility, and PRI modulation.

[0023] Furthermore, the instantaneous parameters include pulse amplitude, carrier frequency, pulse width and arrival direction. The sorter takes the Euclidean norm of the pulse amplitudes in multiple directions in the pulse description word to reduce the dimension, and uses the carrier frequency, pulse width and arrival direction to cluster the pulse description word using the Gaussian kernel function.

[0024] Furthermore, searching for a signal that meets the characteristics of a set radar scanning mode includes: for a quadratic function curve simulating a mechanical scanning radar, finding the highest point of the pulse amplitude in the clustered pulse signal, finding an approximately symmetrical point in a surrounding set range, determining the peak portion of the quadratic function curve, widening along the peak portion and finding a symmetrical point that satisfies the quadratic function curve within a set width interval.

[0025] In summary, the present invention is beneficial in that:

[0026] The integrated radar analysis system provided by the present invention can accurately extract the radar signal of a single radiation source from a large number of intercepted PDWs with a large range of density and serious overlap through a sorter. The sorting is based on amplitude information and can effectively counter the encryption methods of frequency modulation and pulse width modulation. The radar signal simulator can simulate the signals emitted by various radiation sources to generate pulse description words with a specified distribution, which is convenient for evaluating the performance of the sorter algorithm, identifying performance bottlenecks, and guiding the relevant algorithm developers to optimize and improve. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a scenario diagram of radar attack and defense technology in the existing technology.

[0028] Figure 2 It is the algorithm pseudo code diagram of the simulator in the present invention.

[0029] Figure 3 Plot of simulated data for the shape of the PA-TOA sequence generated for the simulator.

[0030] Figure 4 It is a sorting flow chart of the sorter in the present invention.

[0031] Figure 5 This is the pseudo code diagram of the sorter algorithm.

[0032] Figure 6 This is the sorting result diagram of the sorter. DETAILED DESCRIPTION

[0033] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0034] The invention provides a comprehensive radar signal analysis system based on amplitude information, comprising a simulator and a sorter.

[0035] In one aspect, the simulator is used to generate a pulse description word PDW that can specify a distribution, including optional distributions of different pulse amplitudes, the number of objects that appear, and different pulse repetition intervals to generate a pulse amplitude-arrival time sequence that meets requirements.

[0036] The method for the simulator to generate a pulse description word PDW includes:

[0037] Step 1.1: Generate characteristic occurrence points according to the given distribution based on the input parameters (including PRI, probability distribution of target appearance time, etc.). There will be multiple pulse sequences of simulated targets in the entire sequence, and there will also be some introduced noise. In order to describe the time period when a simulated target appears, it is defined as a characteristic occurrence point here, which indicates the position of the time period when the pulse of the simulated target is captured in the entire sequence; when the mechanical scanning radar is simulated, the characteristic occurrence point is the time when the highest point of the quadratic function of the amplitude appears. By default, it is assumed that the number of target appearances randomly satisfies the Poisson distribution. The target appearance situation can be changed according to specific requirements, such as equal interval occurrence and specified period occurrence.

[0038] The parameter λ of the Poisson distribution is the average number of occurrences of random events per unit time. The Poisson distribution is suitable for describing the number of occurrences of random events per unit time. For more general detection modes, the Poisson distribution is preferred here. Different distribution functions can be set for simulation situations, such as average distribution, normal distribution, etc.

[0039] Step 1.2: Establish a signal simulator to simulate the signal amplitude information. First, determine the input parameter information and then generate a continuous quadratic function to simulate the mechanical scanning radar, or generate a discrete straight line to simulate the phased array radar. The input parameters are based on the time point when the target appears, such as the start and end time of the target, and the time period when the target appears (for periodic targets).

[0040] Generally speaking, phased array radars have narrow mainlobe beams and their mainlobe gain is much higher than that of their sidelobes, so a discrete straight line with little fluctuation parallel to the time axis is usually shown on the pulse amplitude-arrival time diagram. Mechanical scanning radars, on the other hand, produce an envelope similar to a quadratic function when scanning, and a quadratic function curve is usually shown on the pulse amplitude-arrival time diagram.

[0041] At this time, by determining the time when the signal occurs, a continuous pulse amplitude-arrival time signal is generated; specifically, the distribution of the pulse signal and the appearance time of the target with radar characteristics can be determined based on the input parameter information. First, the target appearance time is set to the time when the highest point of all quadratic function curves of the target characteristics of the mechanical scanning radar appears, and then stretched to the left and right on the time axis. For the phased array radar, it is set to a pyramid-shaped segmented straight line, and the appearance time is also set to the highest point, and then stretched to both sides on the time axis.

[0042] Step 1.3: Add the generated pulse amplitude-arrival time signals according to the occurrence time of the pulse signal to simulate the overlapping relationship, add the generated multiple pulse amplitude-arrival time signals, simulate the overlap of pulse signals of different targets, and generate an overlapping curve, wherein the overlap of pulse points with different carrier frequencies is not considered. It can be known from the existing radar pulse signal records that the pulse amplitude-arrival time signals generated by multiple targets appearing in the same frequency band will overlap, so that the pulse amplitude-arrival time diagram is not a plurality of discrete quadratic function curves, but a continuous curve with multiple ups and downs.

[0043] Step 1.4: Simulate the pulse repetition interval PRI information. First, determine the pulse-to-pulse modulation method, including PRI stagger, PRI sliding, PRI jitter, PRI pulse group agility, and PRI modulation.

[0044] PRI deviation means: assuming that there are k points in a group of signals, the pulse interval between each group of signals is T1, and the pulse intervals of the k points in each group are t1, t2, t3...t k ;

[0045] PRI slip means that the pulse intervals of k points in each group are t1, t1+Δt, t1+2Δt, t1+3Δt, ... t1+(k-1)Δt;

[0046] PRI jitter means: the interval between single signals is a fixed PRI plus a jitter amount, which is PRI0+δ k where δ k is the random jitter amount;

[0047] PRI pulse group agility means that the repetition frequency remains unchanged within a coherent processing interval, and the repetition frequency can be different in different coherent processing intervals. The interval of each point in the first group of signal points is PRI1, the second group is PRI2, and the kth group is PRI k ;

[0048] PRI modulation means that the intervals between signals are not simply random jitters, but are transformed in a certain modulation function.

[0049] The overlapping curve generated in step 1.3 is intercepted according to the inter-pulse debugging method. Specifically, a pulse timestamp is generated according to the set PRI information, and then the curve is intercepted according to the pulse timestamp to generate a simulated PDW.

[0050] Step 1.5: Considering that there are multiple radiation sources in the actual battlefield environment, each of which may have multiple pulse modes, so that multiple objects can be scanned in the same time period, the above steps 1.2 to 1.4 are repeated multiple times to generate multiple, multi-modulated, and multi-amplitude simulated pulse signals, which are cross-output into the same table and verified by the KS test method to ensure that the simulated pulse signal and the actual observed information satisfy the same distribution.

[0051] KS (Kolmogorov-Smirnow) is a non-parametric statistical test method, which is a test for continuous distribution. This test is often used to compare whether a single sample conforms to a known distribution (compare the cumulative frequency distribution of sample data with a specific theoretical distribution. If the difference between the two is small, it is inferred that the sample is taken from a specific distribution cluster). The two-sample KS test compares the similarity of the cumulative distribution (continuous distribution) of two data sets. The two-sample KS test can be used to detect whether the simulated data and the real recorded data meet the same distribution.

[0052] Step 1.6: Output the generated PDW in time series.

[0053] Reference Figure 2 and Figure 6 The content shown, Figure 2 shows the pseudocode of the simulator algorithm, Figure 6 The simulated data of PA-TOA sequence shape generated by the simulator are shown, which are similar to the measured data at sea. The KS test method is used to test the measured data and the simulated data. The results show that there is no significant difference in the distribution of the two.

[0054] On the other hand, the sorter is used to identify possible radar radiation sources by combining information such as carrier frequency, pulse width, pulse amplitude, and direction of arrival from the pulse description word, and to identify pulse signals belonging to the same radiation source. In actual application scenarios, camouflage and deception can be performed based on the pulse repetition interval information of the identified radiation source. The process of the radar sorter is as follows: Figure 3 As shown, in this embodiment, the data is first sorted, and the PDW generally contains the following information: RF, PW, DOA, TOA, PA. Specifically, the following steps are included:

[0055] Step 2.1: Pre-sort the initial pulse description word PDW output by the simulator. Due to unexpected situations that may cause some independent points that deviate greatly from the overall situation, the PA information in each component is reduced in dimension, and data cleaning is performed to remove abnormal points. Specifically, by clustering the PW, RF, and DOA information using the Gaussian kernel function, clustering the frequency information can classify pulse signals of a certain frequency and a certain pulse width into the same category, which can counter the encryption methods of some frequency modulation information and pulse width modulation information; if there is PA information in multiple directions, the PA information in each direction can be correlated and analyzed, and the Euclidean norm of the PA information with strong correlation can be taken to reduce the dimension and reduce the processing difficulty. Then clean the data.

[0056] Step 2.2: Sort the PA, taking the mechanical scanning radar scanning as an example, find points that meet the characteristics of the quadratic function. The PA information here is a sequence of pulse amplitude-arrival time. Since there are many overlapping radiation source signals in the actual pulse signal record, the signals from the same radiation source are not directly adjacent, but there will be many signals from other radiation sources in the interval between two pulse signals. Perform continuous quadratic function detection on the points after clustering and dimensionality reduction. The specific implementation method is: find the point with the highest PA in the clustering results; and find a point that is approximately symmetrical at -3dB around to determine the peak part of the quadratic function curve. If no point that meets the conditions is found and the peak part cannot be determined, it means that the point is not the maximum value generated by a certain radiation source, then the highest point is removed from the original data and transferred to the new PDW. After determining the peak part, continue to widen it and look for symmetrical points that satisfy the quadratic function curve in the surrounding 20%-80% range. In this embodiment, it is preferred to search for amplitude points with similar widths in the 50% highest amplitude area. The reference width is determined by the carrier frequency, and this parameter is usually searched multiple times to determine the most likely width. Since the 20% part is mostly composed of clutter and is difficult to distinguish, it is not considered for more complex PA areas.

[0057] Step 2.3: Repeat the above operation for the remaining sampling points until the remaining points do not meet the clustering threshold and stop sorting. In step 2.2, fixed frequency radar signals can be directly sorted out. In this step, the remaining signals are clustered to obtain possible frequency diversity signals. The correctness of the above method can be verified by checking the PRI of the above sorting points. Generally speaking, signals from the same radiation source have regular PRI and RF, PW information. After sorting, the signals considered to be from the same radiation source have corresponding characteristics.

[0058] Reference Figure 4-Figure 6 The content shown, Figure 4 The pseudo code of the sorter algorithm is shown. The algorithm runs in Python 3.11 environment and uses measured data from the sea for sorting. The original data contains 9 PA components and a total of 5400 pulse points. The algorithm successfully extracts several pulse sequences from the same radiation source from the aliased signal stream. By verifying the PRI of the sorting results, we successfully identified some pulse waveforms from signal sources such as fishing boats. The algorithm running results are shown in Figure 1. Figure 6 shown.

[0059] Among them, the sorting result A is the initial PDW, B is the single PA component after data cleaning, C, D, and E are the results after clustering, the three coordinate axes are PA, TOA, and class, F is the PA of a single class, G is the pulse point after extracting the envelope and merging, and H is the PRI of the sorting result.

[0060] In addition, there are some pulse sequences whose PRI features are not in our database, but these PRIs also change in a certain pattern, indicating that they may come from the same target. Further inspection of the carrier frequency and pulse width of these pulse points found that the pulse points of some sequences have certain regularity. This shows that our method has a certain effect on the encryption methods against frequency modulation and pulse width modulation.

[0061] Since this method is based on the recognition of amplitude information, it has certain requirements on the integrity of the pulse amplitude signal. For certain use cases, the normalized amplitude information can be used for sorting. At present, the sorter part has a detection effect on the signal of the mechanical scanning radar with complete curve characteristics, and new recognition algorithms still need to be discussed for phased array radars.

[0062] When the algorithm is finished running, multiple sorting results will be returned, which include the pulse amplitude-arrival time curve, and it should be a smooth curve.

[0063] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

Claims

1. A comprehensive radar signal analysis system based on amplitude information, characterized in that: The invention comprises a simulator and a sorter. The simulator generates pulse signals of multiple targets and overlaps them according to set input parameters to output pulse description words for sorting by the sorter. The set input parameters include setting a radar scanning mode. The sorter sorts the pulse description words, reduces the dimension of the pulse signals and clusters them according to the instantaneous parameters of the pulse description words, searches for signals that meet the characteristics of the set radar scanning mode, and outputs pulse signals belonging to the same radiation source.

2. The integrated radar signal analysis system based on amplitude information according to claim 1, characterized in that: The radar scanning mode is set to include one of simulating mechanical scanning radar scanning to generate a quadratic function curve and simulating phased array radar scanning to generate a discrete straight line.

3. The integrated radar signal analysis system based on amplitude information according to claim 2, characterized in that: The target pulse signal generation includes: setting input parameters to determine the target appearance time, setting the target appearance time as the highest point of the quadratic function curve or discrete straight line based on the set radar scanning mode, extending the highest point to both sides on the time axis, and generating the target pulse amplitude-arrival time signal.

4. The integrated radar signal analysis system based on amplitude information according to claim 3 is characterized in that: The pulse amplitude-arrival time signals of multiple targets are added according to the occurrence time of the signals to generate an overlapping curve, and the overlapping curve appears as a single continuous curve with multiple fluctuations on the pulse amplitude-arrival time graph.

5. A comprehensive radar signal analysis system based on amplitude information according to any one of claims 1 to 4, characterized in that: The set input parameters include: the number of target appearances, the probability distribution of target appearance time, the regularity of pulse repetition interval, and the time length of the pulse sequence.

6. The integrated radar signal analysis system based on amplitude information according to claim 1, characterized in that: The method also includes intercepting the overlapping curve, determining the pulse-to-pulse modulation mode based on the pulse repetition interval, generating a pulse time stamp, intercepting the overlapping curve according to the pulse time stamp, and generating a pulse description word.

7. The integrated radar signal analysis system based on amplitude information according to claim 6, characterized in that: The inter-pulse modulation mode includes: one of PRI stagger, PRI sliding, PRI jitter, PRI pulse group agility, and PRI modulation.

8. The integrated radar signal analysis system based on amplitude information according to claim 1, characterized in that: The instantaneous parameters include pulse amplitude, carrier frequency, pulse width and arrival direction. The sorter takes the Euclidean norm of the pulse amplitudes in multiple directions in the pulse description word to reduce the dimension, and clusters the pulse description word using the Gaussian kernel function using the carrier frequency, pulse width and arrival direction.

9. The integrated radar signal analysis system based on amplitude information according to claim 8, characterized in that: The search for a signal that meets the characteristics of a set radar scanning mode includes: for a quadratic function curve simulating a mechanical scanning radar, finding the highest point of the pulse amplitude in the clustered pulse signal, finding an approximately symmetrical point in a surrounding set range, determining the peak portion of the quadratic function curve, widening along the peak portion and finding a symmetrical point that satisfies the quadratic function curve within a set width interval.

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