High duty cycle signal discrimination and rejection method for wide bandwidth spatial receivers

Abstract

The application provides a high duty cycle signal discrimination and suppression method for a wide bandwidth space receiver, comprising the following steps: step 1, background noise statistical processing; step 2, amplitude calculation and peak searching processing; step 3, peak signal space resolution; step 4, single beat statistical quantity generation; step 5, multi-beat statistical quantity generation; step 6, duty cycle calculation and cross-frequency point merging; step 7, high duty cycle signal judgment; and step 8, high duty cycle signal suppression threshold generation and output. The high duty cycle signal discrimination result and the high duty cycle signal suppression threshold generated by the application play a role before the generation of the pulse level detection result, are a beneficial supplement to the traditional background noise statistical threshold and the CFAR threshold, can filter out the high duty cycle signal in the pulse detection stage, can greatly reduce the processing pressure of the subsequent pulse pretreatment and signal sorting, and can improve the interception quality of the receiver to the normal radar pulse signal.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of passive radar receiving processing, in particular to a high-duty-cycle signal discrimination and suppression method for a wideband space receiver. BACKGROUND

[0002] Passive radar does not emit electromagnetic signals by itself, but achieves the detection and discovery of targets by intercepting radar signals of target emitters. With the development and popularization of various electronic devices, the electromagnetic environment becomes more and more complex, and various communication, radar and jamming signals are intertwined, which seriously affects the normal work of passive radar. Especially, mobile communication base stations are widely laid out, and the ubiquitous wideband mobile communication signals are easily detected by passive radar receivers, causing data flow congestion, seriously affecting the interception processing of normal radar pulse signals, and also causing unnecessary processing burden on the sorting and data processing of subsequent radar pulse signals. Therefore, it is particularly important for passive radar receivers to study how to discriminate high-duty-cycle signals such as communication signals and suppress their influence on radar pulse signal interception.

[0003] There is no systematic academic report on the discrimination and suppression of high-duty-cycle signals for passive radar receiving processors. The detection threshold of passive radar receivers is usually determined based on the statistical results of background noise (see James Tusi's Wideband Digital Receiver), and high-duty-cycle communication signals and radar pulse signals are both external input emitter signals, which are easy to be detected compared with completely random background noise signals. Therefore, it is impossible to distinguish high-duty-cycle communication signals and radar pulse signals only by relying on this detection method.

[0004] The most significant difference between radar pulse signals and communication signals is the duty cycle. Generally, radar pulse signals have a low duty cycle, while communication signals are continuous wave signals or large frame length high-duty-cycle signals. One easily thought method is to complete signal detection, and then complete the discrimination of high-duty-cycle signals by duty cycle statistics for a long time (typical value is 1-5 seconds) in the signal sorting or data processing stage. This method is helpful to suppress false alarms in signal sorting and data processing, but it cannot solve the problem of pulse-level data flow congestion after high-duty-cycle signals are detected, and it may still lead to the loss of processing of normal radar pulse signals. SUMMARY

[0005] The present application aims to provide a high-duty-cycle signal discrimination and suppression method for a wideband space receiver, to achieve dynamic monitoring and identification of high-duty-cycle signals such as communication signals, and to use the statistical results for adjusting the detection threshold of the receiver, reducing the detection probability of high-duty-cycle signals, reducing the processing pressure, and reducing the radar pulse signal missing detection problem caused by data flow congestion.

[0006] The application provides a high-duty-cycle signal discrimination and suppression method for a wide bandwidth space receiver, comprising the following steps:

[0007] Step 1, background noise statistical processing: in the case of no signal input, the mean and standard deviation of the random noise amplitude of the receiver are statistically processed to generate a statistical noise threshold;

[0008] Step 2, amplitude calculation and peak searching processing: the collected data of the receiver are processed by transformation to generate multi-frequency point data to be detected; then the multi-frequency point data to be detected are processed by amplitude peak searching point by point to obtain a peak beam amplitude and record adjacent beam amplitudes;

[0009] Step 3, peak signal spatial resolution: according to the system angle measurement principle, the angle range covered by the system is divided into a plurality of azimuth resolution units, and the azimuth resolution unit in which the peak beam is located is estimated by comparing the peak beam amplitude with the adjacent beam amplitudes;

[0010] Step 4, single-beat statistical quantity generation: the peak beam amplitude is compared with the statistical noise threshold point by point to coarsely judge whether the peak beam amplitude contains an external radiation source target signal, and then a single-beat statistical quantity is generated;

[0011] Step 5, multi-beat statistical quantity generation: on the basis of the single-beat statistical quantity, a multi-beat statistical quantity of each frequency point is generated through long-time accumulation processing point by point;

[0012] Step 6, duty cycle calculation and cross-frequency point merging: based on the multi-beat statistical quantity and the azimuth resolution unit, the duty cycle of each frequency point is calculated point by point to obtain the duty cycle of each frequency point;

[0013] Step 7, high-duty-cycle signal judgment: based on the duty cycle of each frequency point, the duty cycle is compared with a preset duty cycle threshold, and if the duty cycle exceeds the duty cycle threshold, it is considered that a high-duty-cycle signal exists in the frequency point;

[0014] Step 8, high-duty-cycle signal suppression threshold generation and output: once it is judged that a high-duty-cycle signal exists, a high-duty-cycle signal suppression threshold is generated based on the multi-beat statistical quantity, which is used as the final detection threshold of the receiver at the frequency point and is used for filtering out the high-duty-cycle signal.

[0015] Further, in step 1, the statistical noise threshold is expressed as:

[0016] TH sig = μ N + c N * σ N

[0017] wherein μ N is the mean of the noise amplitude; σ Nis the standard deviation of the noise amplitude; c N is a coefficient determined according to Rayleigh probability distribution.

[0018] Further, in step 2, the generated multi-frequency point to-be-detected data is expressed as a two-dimensional amplitude matrix data, as shown below:

[0019]

[0020] wherein K is the number of processing frequency points; L is the number of simultaneous multi-beams; y i,j represents the signal amplitude received by the i-th frequency point and the j-th beam.

[0021] Further, in step 4, the elements of the single-beat statistics include {frequency point number, spatial resolution unit number, amplitude value, whether it is a peak value, whether there is a target signal}.

[0022] Further, in step 5, the elements of the multi-beat statistics include {frequency point number, azimuth resolution unit number, peak value beat number N i,a , all peak value amplitude mean μ i,a , all peak value amplitude standard deviation σ i,a , target peak value beat number N i,p , target peak value amplitude mean μ i,p , target peak value amplitude standard deviation σ i,p}.

[0023] As a preferred, in step 5, the recursive processing algorithm is used to calculate the amplitude mean and standard deviation.

[0024] Further, in step 5, the recursive processing algorithm for calculating the amplitude mean and standard deviation is expressed as:

[0025] μ n = μ n-1 + (y n - μ n-1 ) / n

[0026]

[0027] wherein y n represents the n-th amplitude value, μ n represents the statistical mean of the first n amplitude values, and σ n represents the statistical standard deviation of the first n amplitude values.

[0028] Further, in step 6, the method for obtaining the duty cycle of each frequency point is to calculate the ratio of the target peak value beat number N i,p to the total peak value beat number M in each azimuth resolution unit, thereby obtaining the duty cycle of all frequency points, which is expressed as:

[0029] Du i = N i,p / M

[0030] wherein, Du i represents the duty cycle calculation result of the i-th azimuth resolution unit at a certain frequency point; among the duty cycle calculation results of all azimuth resolution units at the frequency point, the maximum duty cycle calculation result is selected as the duty cycle of the frequency point; after obtaining the duty cycles of all frequency points, the frequency points with the same azimuth resolution unit of the maximum duty cycle are associated, and the sum of the duty cycles of these frequency points is used to replace the original duty cycles of the frequency points.

[0031] Further, in step 8, the receiver finally detects the threshold TH det is represented as:

[0032] TH det = μ i,p + c p * σ i,p

[0033] wherein, c p is the up-floating coefficient used by the high-duty-cycle signal suppression threshold.

[0034] As preferred, in step 2, the transformation processing includes FFT transformation and frequency domain beam forming processing.

[0035] In summary, due to the adoption of the above technical solutions, the present application has the following beneficial effects:

[0036] 1. The high-duty-cycle signal discrimination result and the high-duty-cycle signal suppression threshold generated by the present application play a role before the generation of the pulse-level detection result, which is a beneficial supplement to the traditional background noise statistical threshold and the CFAR threshold, and can greatly reduce the processing pressure of the subsequent pulse preprocessing and signal sorting, and improve the interception quality of the receiver to the normal radar pulse signal in the pulse detection stage;

[0037] 2. The present application has certain automatic discrimination ability to the high-duty-cycle signal of the frequency agile signal through the duty cycle statistics of each azimuth resolution unit and the cross-frequency point duty cycle association and merging processing;

[0038] 3. In a complex electromagnetic environment, the amplitude and frequency of the high-duty-cycle signal such as communication may change greatly in a short time, but the target azimuth / tilt cannot change drastically; the present application is based on the azimuth resolution unit to perform the duty cycle statistics, and is more likely to discriminate the high-duty-cycle signal, and has strong robustness;

[0039] 4、The mean value and standard deviation statistics involved in the multi-beat (long time) processing of the application are realized by using a recursive algorithm, which reduces the storage requirement and improves the real-time processing capability, and is suitable for the implementation of a wideband digital receiver on an FPGA;

[0040] 5、The application has universal adaptability to various wideband wide-space receivers with angle measurement capability, including receivers using FFT frequency domain detection or channelization processing, and also including receivers using amplitude comparison angle measurement or phase method angle measurement. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings in the embodiments will be briefly introduced as follows. It should be understood that the following drawings only show some embodiments of the application, and therefore should not be regarded as a limitation on the scope, and other related drawings can also be obtained by those of ordinary skill in the art without creative labor on the basis of these drawings.

[0042] Figure 1 The overall flowchart of the high-duty-cycle signal discrimination and suppression method for a wideband wide-space receiver in the embodiment of the application.

[0043] Figure 2 The detailed flowchart of the high-duty-cycle signal discrimination and suppression method for a wideband wide-space receiver in the embodiment of the application. DETAILED DESCRIPTION

[0044] In order to make the objects, technical solutions and advantages of the embodiments of the application clearer, the technical solutions in the embodiments of the application will be described clearly and completely below in conjunction with the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, rather than all the embodiments. The components of the embodiments of the application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0045] Therefore, the following detailed description of the embodiments of the application provided in the drawings is not intended to limit the scope of the claimed application, but only represents selected embodiments of the application. All other embodiments obtained by those of ordinary skill in the art on the basis of the embodiments in the application without creative labor are within the scope of protection of the application.

[0046] EMBODIMENT

[0047] As shown in Figure 1 , Figure 2 , the embodiment proposes a high-duty-cycle signal discrimination and suppression method for a wideband wide-space receiver, including the following steps:

[0048] Step 1, background noise statistics processing: close the array element radio frequency link, in the absence of signal input, through long time (can be set according to the demand time) statistics, the mean and standard deviation of the receiver random noise amplitude are statistically processed, and the statistical noise threshold is generated; the statistical noise threshold is represented as:

[0049] TH sig = μ N + c N * σ N

[0050] wherein, μ N is the mean of noise amplitude; σ N is the standard deviation of noise amplitude; c N is a coefficient determined according to Rayleigh probability distribution, and the typical value is 0.8-3.

[0051] Step 2, amplitude calculation and peak searching processing: the data collected by the receiver is processed by transformation to generate multi-frequency point data to be detected; in the embodiment, the transformation processing includes FFT transformation and frequency domain beam forming processing; the generated multi-frequency point data to be detected is represented as a two-dimensional amplitude matrix data, as follows:

[0052]

[0053] wherein, K is the number of processing frequency points; L is the number of simultaneous multi-beams; y i,j represents the signal amplitude received by the i-th frequency point and the j-th beam.

[0054] Then, the multi-frequency point data to be detected is processed by amplitude peak searching processing, and only the beam data with the largest amplitude is selected as the peak beam amplitude for each frequency point, so as to obtain the peak beam amplitude and record the adjacent beam amplitude.

[0055] Step 3, spatial resolution of peak value signal: according to the system angle measurement principle, the angle range covered by the system is divided into a plurality of azimuth resolution units (the azimuth resolution unit is not necessarily directly divided into equal parts of the angle range covered by the system, such as phase method angle measurement, which can directly divide the phase difference into a plurality of phase difference intervals, each phase difference interval represents a range of azimuth; and the amplitude comparison method can take the azimuth range between adjacent beams as the azimuth resolution unit, or further subdivide); by comparing the peak beam amplitude and the adjacent beam amplitude, the azimuth resolution unit in which the peak beam is located is estimated.

[0056] Step 4, single beat statistics generation: compare the peak beam amplitude and the statistical noise threshold TH sig for each frequency point, and coarsely judge whether the peak beam amplitude contains the external radiation source target signal: if the peak beam amplitude is greater than TH sig , it is judged that the peak beam amplitude contains the external radiation source target signal, and if the peak amplitude is less than THsig , it is determined that the peak beam amplitude does not contain the external radiation source target signal, and is a pure noise amplitude, and further generates a single-beat statistic; in the embodiment, the single-beat statistic contains "five elements", namely {frequency point number, spatial resolution unit number, amplitude value, whether it is a peak value, and whether there is a target signal};

[0057] Step 5, multi-beat statistic generation: on the basis of the single-beat statistic, multi-frequency point data of M beats are processed by frequency point-by-frequency point long-time accumulation to generate multi-beat statistics of each frequency point; in the embodiment, the elements of the multi-beat statistic include {frequency point number, azimuth resolution unit number, peak value beat number N i,a , all peak value amplitude mean μ i,a , all peak value amplitude standard deviation σ i,a , target peak value beat number N i,p , target peak value amplitude mean μ i,p , target peak value amplitude standard deviation σ i,p}; preferably, in the process of calculating the amplitude mean and standard deviation, a recursive processing algorithm is used to reduce the storage requirement and improve the processing real-time, as shown below:

[0058] μ n = μ n-1 + (y n - μ n-1 ) / n

[0059]

[0060] wherein y n represents the nth amplitude value, μ n represents the statistical mean of the first n amplitude values, and σ n represents the statistical standard deviation of the first n amplitude values.

[0061] Step 6, duty cycle calculation and cross-frequency point merging: based on the multi-beat statistic and the azimuth resolution unit, the duty cycle is calculated frequency point by frequency point to obtain the duty cycle of each frequency point.

[0062] Specifically: the ratio of the target peak value beat number N i,p to the total peak value beat number M is calculated in each azimuth resolution unit, thereby obtaining the duty cycle of all frequency points, which is expressed as:

[0063] Du i = N i,p / M

[0064] wherein Du irepresents the duty cycle calculation result of the i-th azimuth resolution unit of a certain frequency point; among the duty cycle calculation results of all azimuth resolution units of the frequency point, the maximum duty cycle calculation result is selected as the duty cycle of the frequency point; after the duty cycles of all frequency points are obtained, the frequency points with the same azimuth resolution unit of the maximum duty cycle are associated, and the sum of the duty cycles of these frequency points is used to replace the original duty cycles of the frequency points.

[0065] Step 7, high duty cycle signal decision: based on the duty cycles of the frequency points, the duty cycles are compared with a pre-set duty cycle threshold, if the duty cycle exceeds the duty cycle threshold, it is considered that the frequency point has a high duty cycle signal;

[0066] Step 8, high duty cycle signal suppression threshold generation and output: once it is decided that the high duty cycle signal exists, based on the target peak amplitude mean μ i,p and the target peak amplitude standard deviation σ i,p of the multi-beat statistics, the high duty cycle signal suppression threshold is generated, which is used as the final detection threshold TH det of the receiver at the frequency point for filtering out the high duty cycle signal, which is expressed as:

[0067] TH det = μ i,p +c p * σ i,p

[0068] Wherein, c p is the floating coefficient used by the high duty cycle signal suppression threshold, and the typical value is 0.8-3.

[0069] The above only describes the preferred embodiments of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for identifying and suppressing high duty cycle signals in a wideband spatial domain receiver, characterized in that, Includes the following steps: Step 1, Background noise statistical processing: Under the condition of no signal input, the mean and standard deviation of the random noise amplitude of the receiver are statistically analyzed to generate a statistical noise threshold; Step 2, Amplitude Calculation and Peak Search Processing: The receiver-acquired data is transformed to generate multi-frequency data to be detected; then, amplitude peak search processing is performed on the multi-frequency data to be detected point by point to obtain the peak beam amplitude, and the amplitudes of adjacent beams are recorded. Step 3, Spatial resolution of peak signal: Based on the system angle measurement principle, the angular range covered by the system is divided into several azimuth resolution units. By comparing the peak beam amplitude with the amplitude of adjacent beams, the azimuth resolution unit where the peak beam is located is estimated. Step 4, Single-beat statistics generation: The peak beam amplitude is compared with the statistical noise threshold at each frequency point to roughly determine whether the peak beam amplitude contains the target signal of the external radiation source, and then the single-beat statistics are generated. Step 5, Generation of multi-beat statistics: Based on the single-beat statistics, multi-beat statistics for each frequency point are generated through long-term accumulation processing. Step 6, Duty Cycle Calculation and Cross-Frequency Merging: Based on multi-beat statistics and azimuth resolution units, the duty cycle is calculated for each frequency point to obtain the duty cycle of each frequency point; Step 7, High duty cycle signal determination: Based on the duty cycle of each frequency point, compare it with the preset duty cycle threshold. If it exceeds the duty cycle threshold, it is considered that there is a high duty cycle signal at that frequency point. Step 8, High Duty Cycle Signal Suppression Threshold Generation and Output: Once a high duty cycle signal is detected, a high duty cycle signal suppression threshold is generated based on multi-beat statistics and used as the final detection threshold of the receiver at that frequency point to filter out high duty cycle signals. In step 2, the generated multi-frequency point detection data is represented as a two-dimensional amplitude matrix, as shown below: in, K To process the number of frequency points; L The number of simultaneous multi-beams; y i,j Indicates the first i The frequency point, the first j The amplitude of the signal received by each beam; In step 4, the elements of the single-beat statistics include frequency point number, spatial resolution unit number, amplitude value, whether it is a peak value, and whether there is a target signal; In step 5, the elements of the multi-beat statistics include frequency point number, azimuth resolution unit number, and peak beat count. N i,a Average of all peak amplitudes μ i,a Standard deviation of all peak amplitudes σ i,a Target peak beat count N i,p Target peak amplitude mean μ i,p Target peak amplitude standard deviation σ i,p ; In step 5, the mean and standard deviation of the amplitude are calculated using a recursive processing algorithm, expressed as: in, y n Indicates the first n Amplitude value, μ n Indicates the preceding n The statistical mean of each amplitude value σ n Indicates the preceding n The statistical standard deviation of each amplitude value; In step 6, the method for obtaining the duty cycle of each frequency point is to calculate the number of target peak beats in each azimuth resolution cell. N i,p Relative to the total number of peak beats M The ratio of these values ​​is used to obtain the duty cycle for all frequencies, expressed as: Du i = N i,p / M in, Du i Indicates the frequency point i The duty cycle calculation results of each azimuth resolution unit; among the duty cycle calculation results of all azimuth resolution units at this frequency, the maximum duty cycle calculation result is selected as the duty cycle of this frequency; after obtaining the duty cycle of all frequencies, the frequencies with the same azimuth resolution unit where the maximum duty cycle is located are associated, and the sum of the duty cycles of these frequencies is used to replace the original duty cycle of each frequency. In step 8, the receiver finally sets the detection threshold for that frequency. TH det Represented as: in, c p The buoyancy coefficient used for high duty cycle signal suppression threshold.

2. The method for identifying and suppressing high duty cycle signals in a wide bandwidth spatial domain receiver according to claim 1, characterized in that, In step 1, the statistical noise threshold is expressed as: TH sig =μ N +c N σ N in, μ N This represents the average noise amplitude. σ N The standard deviation of the noise amplitude; c N These are the coefficients determined based on the Rayleigh probability distribution.

3. The method for high duty cycle signal identification and suppression in a wide bandwidth spatial domain receiver according to claim 1, characterized in that, In step 2, the transformation process includes FFT transformation and frequency domain beamforming.

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