CN114063021A - Self-adaptive cancellation method for side lobe frequency sweeping interference - Google Patents
Self-adaptive cancellation method for side lobe frequency sweeping interference Download PDFInfo
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- CN114063021A CN114063021A CN202111237025.XA CN202111237025A CN114063021A CN 114063021 A CN114063021 A CN 114063021A CN 202111237025 A CN202111237025 A CN 202111237025A CN 114063021 A CN114063021 A CN 114063021A
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Abstract
The invention relates to a self-adaptive cancellation method for sidelobe frequency sweep interference, and belongs to the field of interference resistance in radar signal processing. The invention determines the interference area by comparing the main channel with the shadow masking channel, and calculates the cancellation coefficient by using the snapshot data of each channel corresponding to the interference position, thereby effectively utilizing the interference data. Compared with the prior art, the invention has the characteristics that: adaptively determining an interference area and obtaining effective interference data, and calculating a weight coefficient by using the effective interference data to improve the cancellation effect; the shadow channel carries out cancellation processing, reduces the interference residue of the shadow channel and avoids the excessive shadow of the shadow channel to the main channel.
Description
Technical Field
The invention belongs to the field of anti-interference in radar signal processing, and relates to a method for realizing self-adaptive cancellation of side lobe frequency sweeping interference. The sweep frequency interference has the characteristics of intermittence, pulse-like performance and randomness, effective snapshot data of the interference cannot be collected by the traditional side lobe cancellation method, calculation of a weight is influenced, the cancellation effect and the convergence speed are further influenced, and excessive image concealment is caused to a main channel by residual strong interference of an image concealment channel. Aiming at the problem, the method adopts the main channel and the shadow channel to carry out combined processing, adaptively acquires interference sample data, can effectively resist sweep-frequency interference, and can be widely applied to the field of radar anti-interference.
Background
The radar anti-interference has become an important content of modern electronic warfare, and side lobe phase cancellation and side lobe ghost are indispensable anti-interference measures of modern radar systems. Sidelobe cancellation is a technical means for inhibiting suppressed active interference, but for smart gap interference, the cancellation system has low convergence speed and cannot cope with the continuous change of external interference. The side lobe suppression is mainly used for suppressing pulse interference or store-and-forward interference with low duty ratio entering from a radar antenna side lobe, but if the side lobe cancellation processing of the suppression channel is not good, the residual interference of the suppression channel can shield the target of the main channel, and further the target detection is influenced. How to effectively inhibit smart intermittent interference is a main problem to be solved urgently in need of radar interference resistance at present.
The sweep frequency bandwidth of the sweep frequency interference signal is larger than the receiving bandwidth of the radar receiver, and the energy of the interference signal can not completely enter the receiver, so that the time domain waveform of the interference signal is changed from continuous wave to intermittent pulse-like waveform which appears intermittently after being detected by the receiver, the appearance frequency is inconsistent with the radar work pace, and the appearance time in the radar receiver is unfixed and shows great randomness. The traditional side lobe cancellation adopts fixed waves to collect interference, effective snapshot data of the interference cannot be collected often, calculation of a weight is influenced, the cancellation effect and the convergence speed are further influenced, interference residues of a shadow channel after cancellation are large, and excessive shadow on a main channel is caused. Therefore, the method combines the main channel and the shadow channel, determines an interference area through self-adaptation, selects interference snapshot data to calculate a weight, realizes real-time following of interference, and can effectively resist sidelobe frequency sweeping type interference.
Disclosure of Invention
Technical problem to be solved
The invention provides a self-adaptive cancellation method for sidelobe sweep frequency interference, which aims at solving the problems that sidelobe cancellation processing cannot acquire interference snapshot effective data in real time due to intermittent, pulse-like and strong-randomness sidelobe sweep frequency interference, cancellation effect is poor, and excessive shadow hiding of a shadow channel on a main channel is caused.
Technical scheme
A self-adaptive cancellation method of side lobe frequency sweep interference is characterized by comprising the following steps:
step 1: respectively carrying out modular processing on the data of the main channel and the data of the shadow channel in a resting area, and multiplying the module value of the main channel by a threshold factor K to obtain a module value threshold of the main channel;
step 2: comparing the module value of the shadow channel with the module value threshold of the main channel, marking the distance unit as an interference position if the module value of the shadow channel is larger than the module value threshold of the main channel, caching the data of the main channel, the shadow channel and all the auxiliary channels corresponding to the distance unit to obtain effective snapshot of the interference;
and step 3: when detecting that the side lobe interference exists and the weight coefficient calculation time slice arrives, reading out interference snapshot data and sending the interference snapshot data to a weight coefficient module for weight coefficient calculation;
and 4, step 4: and in the sidelobe cancellation processing time slice, carrying out sidelobe cancellation processing on the main channel and the shadow eliminating channel by using the weight coefficient obtained by calculation in the rest area.
The further technical scheme of the invention is as follows: and K is 3.0 in the step 1.
The further technical scheme of the invention is as follows: the weight coefficients in step 3 are calculated as follows:
respectively calculating cross-correlation matrixes r of the main channel and the auxiliary channels by assuming that the interference snapshot of the main channel is d and the interference snapshot data of the N auxiliary channels is XXdAutocorrelation matrix R of the auxiliary channelXXFor system robustness, the autocorrelation matrix is loaded diagonally by a loading amount σn(ii) a For autocorrelation matrix (R)XX+σnI) Inverse processing is carried out to obtain the final cancellation weight coefficient Wopt=(RXX+σnI)-1·rXdThe weight coefficient is stored.
The further technical scheme of the invention is as follows: cancellation processing formula d-W in step 4opt*X。
Advantageous effects
The invention provides a self-adaptive cancellation method of sidelobe frequency sweep interference, and for intermittent frequency sweep interference with pulse-like property and strong randomness, effective interference data cannot be acquired by a traditional method, and the cancellation effect is poor due to the influence on weight coefficient calculation, so that an image hiding channel generates excessive image hiding on a main channel, and the target detection is influenced. The invention determines the interference area by comparing the main channel with the shadow masking channel, and calculates the cancellation coefficient by using the snapshot data of each channel corresponding to the interference position, thereby effectively utilizing the interference data, and compared with the prior art, the invention has the following beneficial effects:
1. adaptively determining an interference area and obtaining effective interference data, and calculating a weight coefficient by using the effective interference data to improve the cancellation effect;
2. the shadow channel carries out cancellation processing, reduces the interference residue of the shadow channel and avoids the excessive shadow of the shadow channel to the main channel.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 is a flow chart illustrating the method of the present invention;
FIG. 2 is a graph showing the main channel and shadow channel patterns used in the present invention;
FIG. 3 is a timing diagram illustrating the data processing of the present invention;
FIG. 4 is a flow chart illustrating the weight coefficient calculation of the present invention;
figure 5 is a flow chart illustrating the sidelobe canceling process of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The invention combines the main channel and the shadow masking channel, adaptively judges the position of the interference area by comparing the module values of the two channels, selects snapshot data in the interference area, and obtains the weight coefficient of sidelobe cancellation by using the data. The invention comprises the following steps:
step 1: respectively carrying out modular processing on data of a main channel and data of a shadow channel in a resting area, and multiplying the module value of the main channel by a threshold factor to obtain a module value threshold of the main channel;
step 2: comparing the module value of the shadow channel with the module value threshold of the main channel, marking the distance unit as an interference position if the module value of the shadow channel is larger than the module value threshold of the main channel, caching the data of the main channel, the shadow channel and all the auxiliary channels corresponding to the distance unit to obtain effective snapshot of the interference;
and step 3: when detecting that the side lobe interference exists and the weight coefficient calculation time slice arrives, reading out interference snapshot data and sending the interference snapshot data to a weight coefficient module for weight coefficient calculation;
and 4, step 4: and in the sidelobe cancellation processing time slice, carrying out sidelobe cancellation processing on the main channel and the shadow eliminating channel by using the weight coefficient obtained by calculation in the rest area.
The interference samples of the invention need to be collected in a radar resting area, and the invention is described by taking a main channel and an image hiding channel as examples, wherein the main channel and the image hiding channel are synthesized beams. The number of rest area pulses in a configuration Coherent Processing Interval (CPI) is 1, the number of actual working pulses is M, the time length of the rest area is T, the pulse repetition Period (PRT) is T1, and the number of auxiliary channels of a sidelobe cancellation system is N. The specific implementation method comprises the following steps:
1. in order to avoid clutter data acquisition, interference snapshot needs to be acquired in a radar rest area, radiation is turned off during the radar rest area, and only reception is performed. Meanwhile, in order to cope with random and diverse interference, the weight cancellation coefficient of the current CPI needs to be calculated in real time, so that the weight cancellation coefficient of the current CPI needs to be calculated in a rest area by using the acquired snapshot data. The length T of the rest area needs to include a pulse repetition Period (PRT) T1 and a weight coefficient calculation time T2, namely T > T1+ T2 is met, full coverage of the radar working power can be guaranteed by collected interference data, and a data timing chart is shown in FIG. 3. The actual working pulse is in a time slice of sidelobe cancellation processing, and sidelobe cancellation processing is carried out in the time slice by using the weight coefficient calculated in the rest area.
2. The directional diagrams of the main channel and the shadow channel are shown in fig. 2, the shadow channel is higher than the first side lobe of the main channel by about 3dB, so that the frequency sweep interference entering from the side lobe is larger than that of the main channel, and therefore, the comparison between the shadow channel and the main channel can be utilized to detect the side lobe interference and judge the position of the interference. Firstly, the module processing is carried out on the main channel data and the shadow channel data, the module value of the main channel data is multiplied by a threshold coefficient K to obtain a main channel module value threshold, and the configuration K is 3.0. Comparing the module value of the shadow channel with the module value threshold of the main channel, if the module value of the shadow channel is large, indicating that the distance unit has interference, latching the distance unit number corresponding to the interference, and caching the original data of the main channel, the shadow channel and the N auxiliary channels corresponding to the distance unit number. Meanwhile, the interference detection result is sent to a reading control module to control the reading of the cached interference snapshot data. As shown in step S1 in fig. 1.
3. In step S2 of fig. 1, the read control module counts the number of interference beats per main channel, and when the number of interference beats is greater than N × 4, new interference data will not be received any more, and if the number of collected samples is less than N × 4 within T1, the actual number of samples is used to perform weight coefficient counting. And when the weight coefficient time slice arrives, judging the interference detection result in the step S1, detecting whether side lobe interference exists at present, if so, starting to read interference snapshot data, sequentially reading the stored interference snapshot data, and sending the interference snapshot data to the weight coefficient calculation module for weight coefficient calculation.
4. The weight coefficient calculation is described by taking the main channel weight coefficient calculation as an example, as shown in fig. 4. D is the interference snapshot of the main channel, X is the interference snapshot data of N auxiliary channels, and the cross-correlation matrix r of the main channel and the auxiliary channel is respectively calculatedXdAutocorrelation matrix R of the auxiliary channelXXFor system robustness, to autocorrelationThe matrix is loaded diagonally with a loading amount of sigman. For autocorrelation matrix (R)XX+σnI) Inverse processing is carried out to obtain the final cancellation weight coefficient Wopt=(RXX+σnI)-1·rXdThe weight coefficient is stored. The calculation of the weight coefficient of the hidden channel is consistent with that of the main channel, and the hidden channel data is replaced by the main channel data for calculation, so that the cancellation weight coefficient of the hidden channel can be obtained.
5. In the sidelobe cancellation processing time slice, the weighted sum processing is carried out by using the main channel weight coefficient and the auxiliary channel calculated in the step 4, and then the weighted sum of the auxiliary channel is subtracted from the main channel to obtain the cancellation processing result of the main channel, namely d-WoptX, the same process is applied to the hidden channel to obtain the cancellation result of the hidden channel, and the cancellation process is shown in fig. 5.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present disclosure.
Claims (4)
1. A self-adaptive cancellation method of side lobe frequency sweep interference is characterized by comprising the following steps:
step 1: respectively carrying out modular processing on the data of the main channel and the data of the shadow channel in a resting area, and multiplying the module value of the main channel by a threshold factor K to obtain a module value threshold of the main channel;
step 2: comparing the module value of the shadow channel with the module value threshold of the main channel, marking the distance unit as an interference position if the module value of the shadow channel is larger than the module value threshold of the main channel, caching the data of the main channel, the shadow channel and all the auxiliary channels corresponding to the distance unit to obtain effective snapshot of the interference;
and step 3: when detecting that the side lobe interference exists and the weight coefficient calculation time slice arrives, reading out interference snapshot data and sending the interference snapshot data to a weight coefficient module for weight coefficient calculation;
and 4, step 4: and in the sidelobe cancellation processing time slice, carrying out sidelobe cancellation processing on the main channel and the shadow eliminating channel by using the weight coefficient obtained by calculation in the rest area.
2. The method of claim 1, wherein K in step 1 is 3.0.
3. The method of claim 1, wherein in step 3, the weight coefficients are calculated as follows:
respectively calculating cross-correlation matrixes r of the main channel and the auxiliary channels by assuming that the interference snapshot of the main channel is d and the interference snapshot data of the N auxiliary channels is XXdAutocorrelation matrix R of the auxiliary channelXXFor system robustness, the autocorrelation matrix is loaded diagonally by a loading amount σn(ii) a For autocorrelation matrix (R)XX+σnI) Inverse processing is carried out to obtain the final cancellation weight coefficient Wopt=(RXX+σnI)-1·rXdThe weight coefficient is stored.
4. The method of claim 1, wherein in step 4, the formula d-W is processed for cancellationopt*X。
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CN115390018B (en) * | 2022-07-26 | 2024-04-30 | 西安电子工程研究所 | Method for orienting radar pulse type interference |
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