CN115453466B - Target identification method for resisting variable polarization suppression type interference - Google Patents

Abstract

The invention provides a target identification method for resisting variable polarization suppression type interference, which comprehensively adopts a traditional interference suppression polarization filter and a self-adaptive polarization filter to filter echo signals according to polarization response characteristics of the polarization filter, screens matched detection point pairs exceeding a threshold, and then utilizes time-frequency domain information to jointly identify targets according to different identification amounts of pseudo peaks and target spectrum peaks. The method solves the problem that a large number of false peaks appear in the adaptive polarization filtering process aiming at the variable polarization compression type interference and the problem that the polarization filtering technology designed based on the singularity of the interference polarization scattering matrix is greatly influenced by the signal to noise ratio, has smaller influence by the signal to noise ratio and higher discrimination probability under the condition of the same signal to noise ratio, and provides a technical means for the radar to resist the variable polarization compression type interference.

Description

A target identification method for resisting polarization suppression interference

Technical Field

The invention belongs to the technical field of radars, and in particular relates to a target identification method resistant to variable polarization suppression interference.

Background technique

With the rapid development of modern electronic warfare technology, radar interference is complex and changeable. How to identify targets in an interference environment is a key research direction of current radar technology. Radar target echo information consists of polarization information and the amplitude, time, frequency, phase and azimuth information of the radar signal. When the time domain, frequency domain and spatial domain echo information are difficult to counter interference, the polarization domain information can be used for effective interference countermeasures. In recent years, the performance of radar against fixed polarization interference has been continuously improved, but many traditional polarization interference countermeasures are ineffective for variable polarization interference with constantly changing polarization states. For example, in 2020, Qiang Zhang et al. proposed a method for interference countermeasures using polarization filtering technology. This method has good effects in countering common fixed polarization false target interference and suppression interference, but the anti-interference effect is not good in the case of variable polarization modulation.

In order to counter variable polarization interference, in 2020, Wang Tao and others proposed a method for identifying variable polarization false target interference using the interference polarization scattering matrix. However, since the interference polarization scattering matrix is a sensitive matrix and is easily affected by noise factors, this method is not suitable for countering variable polarization suppression interference. In 2020, Xiong Hui and others designed a universal polarization cancellation technology to counter active interference. This method uses the amplitude of the cross-polarization channel and the co-polarization channel to set the polarization ratio to counter interference. Although this method can achieve good results in countering variable polarization interference, its performance against variable polarization interference is limited under low signal-to-noise ratio conditions.

Summary of the invention

In order to solve the above problems existing in the prior art, the present invention provides a target identification method for resisting polarization suppression interference. The technical problem to be solved by the present invention is achieved by the following technical solutions:

The present invention provides a target identification method for resisting polarization-changing suppression interference, comprising:

Step 1: Get the echo signal;

Step 2: filtering the echo signal using an adaptive polarization filter to obtain a first output signal, and filtering the echo signal using an interference suppression polarization filter to obtain a second output signal;

Step 3: Perform 2D-CFAR detection on the first output signal and the second output signal to confirm a first detection point in the first output signal that exceeds its first threshold, and a second detection point in the second output signal that exceeds its first threshold, and obtain range-Doppler two-dimensional information of the first detection point and the second detection point;

Step 4: Match the distance-Doppler two-dimensional information of the first detection point and the second detection point to identify a pair of matching detection points with the same distance-Doppler two-dimensional information;

Step 5: Calculate the discrimination value of each detection point in the matching detection point pair according to the output signal of the detection point;

Step 6: Determine whether the difference between the discrimination value of each detection point in each matching detection point pair and the discrimination value at the pseudo peak is greater than the respective second thresholds; if so, further determine whether the number of matching detection point pairs is only one, and if so, confirm the matching detection point pair as a real target;

Step 7: If there are multiple matching detection point pairs that are greater than the second threshold, select the matching detection point pair with the largest difference in discrimination value from the pseudo peak and determine the matching detection point pair as the real target.

Optionally, step 5 includes:

Step 5-1: construct a discrimination vector of each detection point according to the output signal of each detection point in the matching detection point pair;

Step 5-2: Calculate the discriminant value of each detection point according to the discriminant vector of each detection point in the matching detection point pair.

Among them, the discrimination vector Y _F of the interference suppression polarization filter is:

The discriminant vector Y _A of the adaptive polarimetric filter is:

Wherein, Y _*H (t) represents the filter output of the horizontal receiving channel, Y _*V (t) represents the filter output of the vertical receiving channel, and “*” represents the horizontal polarization channel (H) or the vertical polarization channel (V).

Optionally, the discrimination value γ _EF of the interference suppression polarization filter and the discrimination value γ _EA of the adaptive polarization filter are respectively:

Optionally, for a pair of matched detection points of the interference suppression polarization filter and the adaptive polarization filter, the discrimination quantities γ _EFI and γ _EAI at the pseudo peak are:

Optionally, step 6 includes:

Step 6-1: Determine whether |γ _EF -45°|>T _E1 and |γ _EA -45°|>T _E2 hold;

Step 6-2: If the formula in 6-1 holds true, further determine whether the number of matching detection point pairs is only one, and if so, confirm that the matching detection point pair is a real target;

Wherein, _TE1 is the second threshold of the matching detection point of the interference suppression polarization filter, and _TE2 is the second threshold of the matching detection point of the adaptive polarization filter.

Optionally, step 7 includes:

If there are multiple matching detection point pairs greater than the second threshold, |γ _EF -45°| and |γ _EA -45°| are calculated, and the matching detection point pair with the largest |γ _EF -45°| and |γ _EA -45°| is selected as the real target.

Beneficial effects of the present invention:

Compared with the prior art, the present invention has the following advantages:

(1) The present invention overcomes the problem of a large number of pseudo peaks appearing when adaptive polarization filtering is used for variable polarization suppression interference.

(2) Compared with the polarization filtering technology designed based on the singularity of the interference polarization scattering matrix, the present invention is less affected by the signal-to-noise ratio and has a higher identification probability under the same signal-to-noise ratio conditions.

The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a target identification method for resisting polarization-changing suppression interference provided by the present invention;

FIG2 is a graph showing a comparison of the identification probabilities of the method of the present invention under different signal-to-noise ratio conditions with an adaptive polarization filter, a universal polarization cancellation technique, and a traditional interference suppression polarization filter in an embodiment of the present invention.

Detailed ways

The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

As shown in FIG1 , a target identification method for resisting polarization-changing suppression interference provided by the present invention includes:

Step 1: Get the echo signal;

Step 2: filtering the echo signal using an adaptive polarization filter to obtain a first output signal, and filtering the echo signal using an interference suppression polarization filter to obtain a second output signal;

The present invention first estimates polarization parameters and sets the frequency response _HF of the interference suppression polarization filter to:

in, represents the estimated value of the polarization angle of the echo signal, Represents the estimated value of the polarization phase angle of the echo signal;

Set the sampling number M, and take N echo signal samples. The frequency response H _An of the adaptive polarization filter of the nth echo signal is:

Wherein, _αn represents the estimated mean polarization amplitude angle of the nth sample, and _δn represents the estimated mean polarization phase angle of the nth sample.

Then use the set filter to filter and get the output signal.

Step 3: Perform 2D-CFAR detection on the first output signal and the second output signal to confirm a first detection point in the first output signal that exceeds its first threshold and a second detection point in the second output signal that exceeds its first threshold, and obtain range-Doppler two-dimensional information of the first detection point and the second detection point;

The first threshold in the first output signal and the first threshold in the second output signal are both preset values, and the two may be the same or different.

Step 4: Match the distance-Doppler two-dimensional information of the first detection point and the second detection point to identify a pair of matching detection points with the same distance-Doppler two-dimensional information;

Step 5: Calculate the discrimination value of each detection point in the matching detection point pair according to the output signal of the detection point;

Step 5 includes:

Step 5-1: construct a discrimination vector of each detection point according to the output signal of each detection point in the matching detection point pair;

Step 5-2: Calculate the discriminant value of each detection point according to the discriminant vector of each detection point in the matching detection point pair.

Among them, the discrimination vector Y _F of the interference suppression polarization filter is:

The discriminant vector Y _A of the adaptive polarimetric filter is:

Wherein, Y _*H (t) represents the filter output of the horizontal receiving channel, Y _*V (t) represents the filter output of the vertical receiving channel, and “*” represents the horizontal polarization channel (H) or the vertical polarization channel (V).

The discrimination vector can be used to calculate the discrimination value γ _EF of the traditional interference suppression polarization filter and the discrimination value γ _EA of the adaptive polarization filter:

Then the discrimination values γ _EFI and γ _EAI at the pseudo peaks in the output channels of the traditional interference suppression polarization filter and the adaptive polarization filter are:

The discrimination values γ _EFs and γ _EAs at the target spectrum peak in the output channel of the traditional interference suppression polarization filter and the adaptive polarization filter are:

in, _PFs* and PFI _* represent the target and interference signal output powers of the traditional interference suppression polarization filter, and _PAs* and _PAI* represent the target and interference signal output powers of the adaptive polarization filter. Since the target polarization scattering matrix is non-singular, both _PFsV - _PFsH and _PAsV - _PAsH are non-zero, and _γEFs and _γEAs do not have the characteristic of approaching 45°.

Therefore, the present invention can make a determination based on the difference between the identification amount at the pseudo peak and the identification amount at the target spectrum peak.

Step 6: Determine whether the difference between the discrimination value of each detection point in each matching detection point pair and the discrimination value at the pseudo peak is greater than the respective second thresholds; if so, further determine whether the number of matching detection point pairs is only one, and if so, confirm the matching detection point pair as a real target;

The step 6 comprises:

Step 6-1: Determine whether |γ _EF -45°|>T _E1 and |γ _EA -45°|>T _E2 hold;

Step 6-2: If the formula in 6-1 holds true, further determine whether the number of matching detection point pairs is only one, and if so, confirm that the matching detection point pair is a real target;

Among them, _TE1 is the second threshold of the matching detection point of the interference suppression polarization filter, and _TE2 is the second threshold of the matching detection point of the adaptive polarization filter.

Step 7: If there are multiple matching detection point pairs that are greater than the second threshold, select the matching detection point pair with the largest difference in discrimination value from the pseudo peak and determine the matching detection point pair as the real target.

In this step, if there are multiple matching detection point pairs greater than the second threshold, |γ _EF -45°| and |γ _EA -45°| are calculated, and the matching detection point pair with the largest |γ _EF -45°| and |γ _EA -45°| is selected to be determined as the real target.

The present invention proposes a target identification method that is resistant to variable polarization suppression interference. According to the polarization response characteristics of the polarization filter, a traditional interference suppression polarization filter and an adaptive polarization filter are used to filter the echo signal, and matching detection point pairs exceeding the threshold are screened. Then, according to the difference between the identification amount at the pseudo peak and the identification amount of the target spectrum peak, the target is jointly identified using time-frequency domain information. The present invention overcomes the problem of a large number of pseudo peaks appearing when the adaptive polarization filter is used for variable polarization suppression interference, and the problem that the polarization filtering technology designed based on the singularity of the interference polarization scattering matrix is greatly affected by the signal-to-noise ratio. The present invention is less affected by the signal-to-noise ratio and has a higher identification probability under the same signal-to-noise ratio conditions, providing a technical means for radar to counter variable polarization suppression interference.

The present invention is further described in detail below in conjunction with a simulation example.

Simulation example:

In order to verify the effectiveness of the method of the present invention, the inventors conducted a simulation experiment using MATLAB software.

The variable polarization noise suppression interference of the simulation experiment uses actual collected data, and compares the identification probability of the method of the present invention with the adaptive polarization filtering method proposed by Qiang Zhang et al. in 2020, the general polarization filtering technology designed by Xiong Hui et al., and the traditional interference suppression polarization filter method, with a Monte Carlo number of 10,000 times.

The identification probabilities of the adaptive polarization filter, the general polarization cancellation technology, the traditional interference suppression polarization filter and the method of the present invention under different signal-to-noise ratio conditions are shown in Figure 2. It can be seen that under the same signal-to-noise ratio conditions, the identification probability of the method proposed in the present invention is higher and the performance is better; the performance of the general polarization filtering technology decays rapidly under low signal-to-noise ratio conditions; the performance of the traditional interference suppression polarization filter algorithm is average; the adaptive polarization filtering method has the worst performance because the pseudo-peak problem cannot be solved. The experimental results show that the algorithm proposed in this article is very effective in combating variable polarization suppression interference.

In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other variations of the disclosed embodiments by reviewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality of components or steps.

The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims (3)

1. A target identification method for resisting polarization-changing suppression interference, characterized by comprising: Step 1: Get the echo signal; Step 2: filtering the echo signal using an adaptive polarization filter to obtain a first output signal, and filtering the echo signal using an interference suppression polarization filter to obtain a second output signal; Step 3: Perform 2D-CFAR detection on the first output signal and the second output signal to confirm a first detection point in the first output signal that exceeds its first threshold, and a second detection point in the second output signal that exceeds its first threshold, and obtain range-Doppler two-dimensional information of the first detection point and the second detection point; Step 4: Match the distance-Doppler two-dimensional information of the first detection point and the second detection point to identify a pair of matching detection points with the same distance-Doppler two-dimensional information; Step 5: Calculate the discrimination value of each detection point in the matching detection point pair according to the output signal of the detection point; Step 6: Determine whether the difference between the discrimination value of each detection point in each matching detection point pair and the discrimination value at the pseudo peak is greater than the respective second thresholds; if so, further determine whether the number of matching detection point pairs is only one, and if so, confirm the matching detection point pair as a real target; Step 7: If the number of matching detection point pairs greater than the second threshold is multiple, then select the matching detection point pair with the largest difference in the discrimination amount at the pseudo peak, and determine the matching detection point pair as the true target; Step 2 includes: Set the frequency response _HF of the interference suppression polarization filter to: in, represents the estimated value of the polarization angle of the echo signal, Represents the estimated value of the polarization phase angle of the echo signal; Set the sampling number M, and take N echo signal samples. The frequency response H _An of the adaptive polarization filter of the nth echo signal is: Wherein, α _n represents the estimated mean polarization amplitude angle of the nth sample, and δ _n represents the estimated mean polarization phase angle of the nth sample; Using a set adaptive polarization filter to filter the echo signal to obtain a first output signal, and using a set interference suppression polarization filter to filter the echo signal to obtain a second output signal; Step 5 includes: Step 5-1: construct a discrimination vector of each detection point according to the output signal of each detection point in the matching detection point pair; Step 5-2: Calculate the discriminant value of each detection point according to the discriminant vector of each detection point in the matching detection point pair; The discrimination vector Y _F of the interference suppression polarization filter is: The discriminant vector Y _A of the adaptive polarimetric filter is: Wherein, Y _*H (t) represents the filter output of the horizontal receiving channel, Y _*V (t) represents the filter output of the vertical receiving channel, and “*” represents the horizontal polarization channel (H) or the vertical polarization channel (V); The discrimination value _γEF of the interference suppression polarization filter and the discrimination value _γEA of the adaptive polarization filter are respectively: The matching detection point pair of the interference suppression polarization filter and the adaptive polarization filter, the discrimination quantity γ _EFI and γ _EAI at the pseudo peak is: 2. The target identification method for resisting polarization-changing suppression interference according to claim 1, characterized in that step 6 comprises: Step 6-1: Determine whether |γ _EF -45°|>T _E1 and |γ _EA -45°|>T _E2 hold; Step 6-2: If the formula in 6-1 holds true, further determine whether the number of matching detection point pairs is only one, and if so, confirm that the matching detection point pair is a real target; Among them, _TE1 is the second threshold of the matching detection point of the interference suppression polarization filter, and _TE2 is the second threshold of the matching detection point of the adaptive polarization filter. 3. The target identification method for resisting polarization-changing suppression interference according to claim 2, characterized in that step 7 comprises: If there are multiple matching detection point pairs greater than the second threshold, |γ _EF -45°| and |γ _EA -45°| are calculated, and the matching detection point pair with the largest |γ _EF -45°| and |γ _EA -45°| is selected as the real target.