CN109541549B - Intermittent sampling forwarding interference suppression method based on EMD and sparse signal processing - Google Patents
Intermittent sampling forwarding interference suppression method based on EMD and sparse signal processing Download PDFInfo
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- CN109541549B CN109541549B CN201811173267.5A CN201811173267A CN109541549B CN 109541549 B CN109541549 B CN 109541549B CN 201811173267 A CN201811173267 A CN 201811173267A CN 109541549 B CN109541549 B CN 109541549B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses an intermittent sampling forwarding interference suppression method based on EMD and sparse signal processing. The method and the device can determine the position of the intermittently sampled and forwarded interference signal in the radar echo signal, and can effectively ensure the signal reconstruction effect under the condition of data loss.
Description
Technical Field
The invention relates to the field of radar signal anti-interference, in particular to an intermittent sampling forwarding interference suppression method based on EMD and sparse signal processing.
Background
In modern informatization war, the countermeasure of radar is more and more intense, especially the radar comprehensive interference technology developed at the end of 20 th century has complex interference signals, variable tactical measures and strong timeliness, and can seriously threaten the normal work of radar. Active radar interference is divided into suppressed interference and deceptive interference, and various interference patterns require that the radar can be accurately identified, so that corresponding countermeasures can be taken. The intermittent sampling forwarding interference is a mainstream interference pattern at present, on one hand, noise suppression can be carried out on the radar, and meanwhile, speed and distance deception can be carried out on multiple false targets. Therefore, there is a need for a radar with superior anti-jamming capability.
Disclosure of Invention
In order to overcome at least one defect in the prior art, the invention provides an intermittent sampling forwarding interference suppression method based on EMD and sparse signal processing.
The present invention aims to solve the above technical problem at least to some extent.
The invention mainly aims to inhibit intermittent sampling forwarding interference by adopting a method of combining EMD and sparse signal processing.
A further object of the invention is to improve the ability of radar to extract refined features.
A third object of the invention is to improve the ability of the radar to identify target signals with high quality.
In order to solve the technical problems, the technical scheme of the invention is as follows: an intermittent sampling forwarding interference suppression method based on EMD and sparse signal processing comprises the following steps:
s1: inputting the disturbed original signal x (t) into the system;
s2: decomposing the interfered signals by adopting an empirical mode decomposition method EMD to obtain an average trend, determining the part of signals which are more than or equal to the average trend as the positions of the intermittent sampling forwarding interference signals, and obtaining sparse target signals after sampling and eliminating the interference signals;
s3: and carrying out sparse signal processing on the obtained sparse target signal to obtain a reconstructed signal.
Preferably, the S1 inputs the interfered original signal x (t) into the system and processes r 0 Initializing to obtain initialized original signal r 0 ：
r 0 (t)＝x(t)。
Preferably, in step S2, an empirical mode decomposition method EMD is used to decompose the interfered signal to obtain an average trend, the part of the signal greater than or equal to the average trend is determined as the position of the intermittent sampling forwarding interference signal, and the specific steps of obtaining the sparse target signal after sampling and eliminating the interference signal are as follows:
s201: finding out all maximum value points and all minimum value points of an original signal x (t);
s202: fitting all maximum value points into an upper envelope line on the original data sequence by using a cubic spline function, and fitting all minimum value points into a lower envelope line on the original data sequence by using the cubic spline function;
s203: calculate the mean value of the upper and lower envelope, and is recorded as m 1 (t)；
S204: the mean value m of the envelope is subtracted from the original signal x (t) 1 (t) obtaining a new data sequence h with low frequency removed 1 (t), i.e. h 1 (t)＝x(t)-m 1 (t)；
S205: repeating the steps S201 to S204 for k times until h 1 (t) meets the definition requirement of intrinsic mode function IMF to obtain component c of the 1 st intrinsic mode function 1 (t), which represents the highest frequency component in the original signal x (t);
s206: c is to 1 (t) separating from x (t) to obtain a difference signal r with low frequency components removed 1 (t)
Namely: r is 1 (t)＝x(t)-c 1 (t)
S207: will r is 1 (t) repeating the steps S201-S206 for n times as the original data to obtain the component c of the nth intrinsic mode function IMF n (t)：
When a given termination condition is met, the loop ends;
s208: from the formulas in S206 and S207, one can obtain:
wherein r is n (t) is a residual term representing the average trend of the signal;
s209: taking the residual term as the adaptive threshold Th (t), i.e. Th (t) = r n (t)；
S210: if the value of the original signal x (t) is greater than or equal to the adaptive threshold Th (t), judging the original signal x (t) as an interference signal, and if the value of the original signal x (t) is less than the adaptive threshold Th (t), judging the original signal x (t) as a normal echo signal;
s211: sampling the part of echo signals which are judged to contain interference signals by adopting a 80MHz sampling rate, removing sampling points which are more than or equal to an adaptive threshold Th (t), and reserving the sampling points which are less than the adaptive threshold Th (t) to obtain sparse target signals with interference elimination;
preferably, the termination condition of step S207 is r n (t) is a monotonic function.
Preferably, the step S3 of performing sparse signal processing on the obtained target signal to obtain a reconstructed signal includes:
s301: abstract expression is carried out on a target signal after interference signals are removed based on EMD:
y＝Θφx+N
wherein x represents the backscattering coefficient of the target, y represents the measured echo, phi represents the radar observation matrix, theta represents the interference rejection matrix, and N represents the system noise;
s302: the backscattering coefficient x of the target is optimized:
wherein λ is a regularization parameter;
s303: and obtaining a reconstructed signal after sparse signal processing.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that: the EMD is adopted to analyze the interfered radar signals, so that the positions of the interference signals can be determined, and the effect is better than that of the traditional mode. By adopting the sparse signal processing technology, the sparse echo signal obtained by EMD processing, sampling and interference signal elimination can be effectively reconstructed, and the processing effect under the condition of data loss can be effectively ensured.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
the technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
FIG. 1 shows a flow chart of the present invention, which includes the steps of:
s1: inputting the interfered original signal x (t) into the system, and comparing r 0 And (3) initializing: obtaining an initialized original signal r 0 ：
r 0 (t)＝x(t)。
S2: decomposing the interfered signals by adopting an empirical mode decomposition method EMD to obtain an average trend, determining the part of signals which are more than or equal to the average trend as the positions of the intermittent sampling forwarding interference signals, and obtaining sparse target signals after sampling and eliminating the interference signals;
s201: finding out all maximum value points and all minimum value points of an original signal x (t);
s202: fitting all maximum value points into an upper envelope line on the original data sequence by using a cubic spline function, and fitting all minimum value points into a lower envelope line on the original data sequence by using the cubic spline function;
s203: calculate the mean value of the upper and lower envelopes, denoted m 1 (t)；
S204: the mean value m of the envelope is subtracted from the original signal x (t) 1 (t) obtaining a new data sequence h with low frequency removed 1 (t), i.e. h 1 (t)＝x(t)-m 1 (t)；
S205: repeating the steps S201-S204 k times until h 1 (t) meets the definition requirement of intrinsic mode function IMF to obtain component c of the 1 st intrinsic mode function 1 (t), which represents the highest frequency component in the original signal x (t);
s206: c is to 1 (t) separating from x (t) to obtain a difference signal r from which the high frequency component is removed 1 (t)
Namely: r is 1 (t)＝x(t)-c 1 (t)
S207: will r is 1 (t) repeating S201-S207 for n times as the original data to obtain the nth IMF component c n (t)：
When satisfy r n (t) is a monotonic function, and the cycle ends;
s208: from the formulas in S206 and S207, one can obtain:
wherein r is n (t) is a residual term representing the average trend of the signal;
s209: the residual term is set as the adaptive threshold Th (t), i.e. Th (t) = r n (t)；
S210: if the value of the original signal x (t) is greater than or equal to the adaptive threshold Th (t), judging the original signal x (t) as an interference signal, and if the value of the original signal x (t) is less than the adaptive threshold Th (t), judging the original signal x (t) as a normal echo signal;
s211: sampling the echo signals which are judged to contain the interference signals by adopting a sampling rate of 80MHz, removing sampling points which are more than or equal to the adaptive threshold Th (t), and reserving the sampling points which are less than the adaptive threshold Th (t) to obtain sparse target signals with interference elimination;
s3: and carrying out sparse signal processing on the obtained sparse target signal to obtain a reconstructed signal.
S301: abstract expression is carried out on a target signal after interference signals are removed based on EMD:
y＝Θφx+N
wherein x represents the backscattering coefficient of the target, y represents the measured echo, phi represents a radar observation matrix, theta represents an interference rejection matrix, and N represents system noise;
s302: the backscattering coefficient x of the target is optimized:
wherein λ is a regularization parameter;
s303: and obtaining a reconstructed signal after sparse signal processing.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. This need not be, nor should it be exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (4)
1. An intermittent sampling forwarding interference suppression method based on EMD and sparse signal processing is characterized in that: the method comprises the following steps:
s1: inputting the disturbed original signal x (t) into the system;
s2: decomposing the interfered signals by adopting an empirical mode decomposition method EMD to obtain an average trend, determining the part of signals which are more than or equal to the average trend as the positions of the intermittent sampling forwarding interference signals, and obtaining sparse target signals after sampling and eliminating the interference signals;
s3: carrying out sparse signal processing on the obtained sparse target signal to obtain a reconstructed signal;
in the S2, an empirical mode decomposition method EMD is adopted to decompose the interfered signals to obtain an average trend, the part of signals with the average trend or more are determined as the positions of the intermittent sampling forwarding interference signals, and the interference signals are sampled and removed to obtain sparse target signals, wherein the method comprises the following specific steps:
s201: finding out all maximum value points and all minimum value points of an original signal x (t);
s202: fitting all maximum value points into an upper envelope line on the original data sequence by using a cubic spline function, and fitting all minimum value points into a lower envelope line on the original data sequence by using the cubic spline function;
s203: calculate the mean value of the upper and lower envelope, and is recorded as m 1 (t)；
S204: the mean value m of the envelope is subtracted from the original signal x (t) 1 (t) obtaining a new data sequence h with low frequency removed 1 (t), i.e. h 1 (t)＝x(t)-m 1 (t)；
S205: repeating the steps S201-S204 k times until h 1 (t) meets the definition requirement of intrinsic mode function IMF to obtain component c of the 1 st intrinsic mode function 1 (t), which represents the highest frequency component in the original signal x (t);
s206: c is to 1 (t) separating from x (t) to obtain a difference signal r from which the high frequency component is removed 1 (t) is as follows:
r 1 (t)＝x(t)-c 1 (t)
s207: will r is 1 (t) repeating the steps S201-S206 for n times as the original data to obtain the component c of the nth intrinsic mode function IMF n (t)：
When a given termination condition is met, the loop ends;
s208: from the formulas in S206 and S207, one can obtain:
wherein r is n (t) is a residual term representing the average trend of the signal;
s209: taking the residual term as the adaptive threshold value Tht), i.e. Th (t) = r n (t)；
S210: if the value of the original signal x (t) is greater than or equal to the adaptive threshold Th (t), judging the original signal x (t) as an interference signal, and if the value of the original signal x (t) is less than the adaptive threshold Th (t), judging the original signal x (t) as a normal echo signal;
s211: and sampling the part of echo signals judged to contain the interference signals by adopting a sampling rate of 80MHz, removing sampling points which are more than or equal to the adaptive threshold Th (t), and reserving the sampling points which are less than the adaptive threshold Th (t) to obtain the interference-removed sparse target signals.
2. The intermittent sampling forwarding interference suppression method based on EMD and sparse signal processing as claimed in claim 1, wherein: s1, inputting the interfered original signal x (t) into the system, and comparing r 0 Initializing to obtain initialized original signal r 0 ：
r 0 (t)＝x(t)。
3. The method for suppressing the intermittent sampling forwarding interference based on the EMD and the sparse signal processing according to claim 1, wherein: the termination condition of step S207 is r n (t) is a monotonic function.
4. The method for suppressing the intermittent sampling forwarding interference based on the EMD and the sparse signal processing according to claim 1, wherein: the step S3 of performing sparse signal processing on the obtained target signal to obtain a reconstructed signal includes the specific steps of:
s301: abstract expression is carried out on a target signal after interference signals are removed based on EMD:
y＝Θφx+N
wherein x represents the backscattering coefficient of the target, y represents the measured echo, phi represents the radar observation matrix, theta represents the interference rejection matrix, and N represents the system noise;
s302: the backscattering coefficient x of the target is optimized:
wherein λ is a regularization parameter;
s303: and obtaining a reconstructed signal after sparse signal processing.
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