Echo signal processing method and rotor UAV detection method

Abstract

The present disclosure provides a method for processing echo signals, including: S1, pre-processing echo signals, wherein the echo signals include translational signals generated by the movement of the target body and micro-Doppler signals generated by the micro-motion of the target, and the translational signals are linear frequency modulation signals; S2, constructing a rotation operator, and rotating the echo signal by a predetermined angle according to the rotation operator, so that the energy of the translational signal is projected on the range axis to reach the narrowest width; S3, scanning the echo signal in a direction perpendicular to the range axis to obtain the parameter space of the echo signal energy; S4, determining the translational signal according to the peak value of the parameter space and eliminating the translational signal to obtain the micro-Doppler signal. The present disclosure accurately estimates the translational signal from the mixed echo signal and eliminates it, thereby improving the signal-to-noise ratio of weak targets and enhancing the detection performance of the radar system for slow "low, slow and small" targets.

Description

Technical Field

[0001] The present disclosure relates to the technical field of radar signal processing, and in particular to a method for processing echo signals and a method for detecting a rotary-wing unmanned aerial vehicle. Background Art

[0002] With the rapid development of information technology, the number of low-altitude aircraft, typically rotary-wing UAVs, has exploded. The problems of air defense safety, flight safety, and public safety caused by the "illegal flying" and "random flying" of consumer-grade UAVs have always been a looming shortcoming in my country's air defense system, posing a threat to public safety and even national security. Since microwave signals can effectively penetrate clouds, dust, and smoke, low-altitude surveillance radars can effectively detect "high, slow, and small", "low, fast, and small", or "low, slow, and large" rotary-wing UAV targets all day and all weather, and can quickly scan and obtain a large amount of data. In order to achieve accurate identification and classification of targets, the key issue lies in the selection and extraction technology of the target's diverse features. Therefore, the use of Doppler radar processing to achieve the detection and identification of "low, slow, and small" targets has received widespread attention.

[0003] The echo of a micro-motion target in the radar can be simplified into two signal components. One component is the translational component caused by the movement of the target body, and the echo of this component is represented by a polynomial phase signal. The other component is the micro-Doppler signal due to the micro-motion of the target, and this component is represented by a sinusoidal frequency modulation signal. These two components are mixed to form a polynomial-sine frequency modulation (PPS-SFM) hybrid form.

[0004] Due to the translation of the rotor UAV, the center frequency of the micro-Doppler signal component attached to the mixed signal changes, and a serious tilt occurs in the time-distance direction as time changes, causing the existing rotor UAV micro-motion parameter estimation method to fail. Moreover, when the translation speed of the rotor UAV is too large, the Doppler shift caused by the translation of the rotor UAV body and the spectrum broadening effect caused by the rotor micro-motion will be superimposed on each other, resulting in serious Doppler ambiguity. Therefore, this type of mixed moving target is a hot spot and a difficult problem in the current micro-motion target detection. Summary of the invention

[0005] In view of the above-mentioned defects in the prior art, the present invention provides a method for processing echo signals, which aims at the problem of detecting rotorcraft UAV targets in a slow-motion state, fully utilizes the characteristic differences between the components of the rotorcraft UAV target body and the rotor echo signal, and adopts targeted analysis methods for two different forms of signals, namely the polynomial signal generated by the UAV target body and the sinusoidal frequency-modulated signal generated by the UAV rotor. The motion parameters of the target body are accurately estimated from the mixed signal, and the energy concentration of the slow rotorcraft UAV target in the rotational transformation domain is improved by compensating for the slow motion characteristics of the target, thereby improving the signal-to-noise ratio of weak targets, and enhancing the detection performance of the radar system for slow "low, slow and small" targets such as rotorcraft UAVs.

[0006] The present invention provides a method for processing echo signals, comprising: S1, pre-processing echo signals, wherein the echo signals include translational signals generated by target body motion and micro-Doppler signals generated by target micro-motion, and the translational signals are linear frequency modulation signals; S2, constructing a rotation operator, and rotating the echo signals by a predetermined angle according to the rotation operator, so that the broadening of the translational signal energy projected on the range axis reaches the narrowest; S3, scanning the echo signals in a direction perpendicular to the range axis to obtain a parameter space of the echo signal energy; S4, determining the translational signal according to a peak value of the parameter space and eliminating the translational signal to obtain the micro-Doppler signal.

[0007] Optionally, the pre-processing of the echo signal in step S1 includes using a sliding window to truncate the echo data sequence x(n), n=1, L, N into an echo sequence group.

[0008] Optionally, the expression of the rotation operator in step S2 is:

[0009] φ R (t) = exp(Φ υ t+Φ0), where φ R is the rotation operator, Φ υ is the rotation angle of the echo signal, Φ0 is the initial angle of the echo signal, and t is the time series of the echo signal.

[0010] Optionally, the corresponding relationship of the parameters in the parameter space of the echo signal energy in step S3 is: in, is the analytical signal of the rotated echo signal, is the parameter space of energy in the echo signal, is the rotation angle of the echo signal, Φ0 is the initial angle of the echo signal, and t is the time series of the echo signal;

[0011] Said in, Sd is the analytical signal of the echo signal, is the complex form of the Gaussian window function with a time width of σ;

[0012] Said g σ (t) is a Gaussian window function with a time width of σ.

[0013] Optionally, the micro-Doppler signal is a sinusoidal frequency-modulated signal.

[0014] The present invention also provides a detection method for a rotary-wing UAV, comprising: acquiring an echo signal sent by a moving target; processing the echo signal using the above-mentioned echo signal processing method to determine whether a corresponding micro-Doppler signal can be obtained, and if so, determining that the moving target is a rotary-wing UAV.

[0015] The echo signal processing method disclosed in the present invention aims at the problem of detecting rotor UAV targets in a slow-motion state, makes full use of the characteristic differences between the rotor UAV target body and the rotor echo signal components, adopts targeted analysis methods for two different forms of signals, namely the polynomial signal generated by the UAV target body and the sinusoidal frequency-modulated signal generated by the UAV rotor, accurately estimates the target body motion parameters from the mixed echo signal, and improves the energy concentration of the slow rotor UAV target in the rotational transformation domain by compensating for the slow motion characteristics of the target, thereby improving the signal-to-noise ratio of weak targets and enhancing the detection performance of the radar system for slow "low, slow and small" targets such as rotor UAVs.

[0016] Compared with the traditional moving target parameter estimation method, the echo signal processing method disclosed in the present invention has high calculation efficiency and basically meets the real-time requirements of actual engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart schematically shows a method for processing an echo signal according to an embodiment of the present disclosure;

[0018] Figure 2 Schematically shows a relationship diagram of echo signal distance-time domain according to an embodiment of the present disclosure;

[0019] Figure 3 The working mechanism diagram of the rotation operator according to the embodiment of the present disclosure is schematically shown;

[0020] Figure 4 Schematically showing a parameter space diagram of echo signal energy in a rotation domain according to an embodiment of the present disclosure;

[0021] Figure 5A schematic diagram showing the comparison of the detection accuracy of the front and rear rotor drones after the translational signal compensation according to an embodiment of the present disclosure; DETAILED DESCRIPTION

[0022] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0023] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0024] Figure 1 A flowchart schematically shows a method for processing an echo signal according to an embodiment of the present disclosure;

[0025] The embodiment of the present disclosure provides a method for processing an echo signal, such as Figure 1 As shown, including:

[0026] S1, using a sliding window of length L to intercept the echo data sequence x(n), n=1, L, N into an echo sequence group, thereby completing the preprocessing of the echo signal, wherein the echo signal includes a translation signal generated by the target body motion and a micro-Doppler signal generated by the target micro-motion, the translation signal is a linear frequency modulation signal, and the micro-Doppler signal is a sinusoidal frequency modulation signal;

[0027] S2, construct the rotation operator, whose expression is φ R (t) = exp(Φ υ t+Φ0), where φ R is the rotation operator, Φ v is the rotation angle of the echo signal, Φ0 is the initial angle of the echo signal, and t is the time series of the echo signal, so that after the echo signal is rotated by a predetermined angle according to the rotation operator, the width of the translation signal energy projected on the range axis reaches the narrowest;

[0028] S3, scanning the echo signal in a direction perpendicular to the range axis to obtain the parameter space of the echo signal energy;

[0029] S4, determining the translation signal according to the peak value of the parameter space and eliminating the translation signal to obtain the micro-Doppler signal.

[0030] In some embodiments, the corresponding relationship of the parameters in the parameter space of the echo signal energy in step S3 is: in, is the analytical signal of the rotated echo signal, is the parameter space of energy in the echo signal, Φ v is the rotation angle of the echo signal, Φ0 is the initial angle of the echo signal, in, S d is the analytical signal of the echo signal, is the complex form of the Gaussian window function with a time width of σ, g σ (t) is a Gaussian window function with a time width of σ.

[0031] Figure 2 Schematically shows a relationship diagram of echo signal distance-time domain according to an embodiment of the present disclosure;

[0032] Figure 3 The working mechanism diagram of the rotation operator according to the embodiment of the present disclosure is schematically shown;

[0033] Figure 4 Schematically showing a parameter space diagram of echo signal energy in a rotation domain according to an embodiment of the present disclosure;

[0034] In one embodiment, it is assumed that there is a point target at a distance of 200 m from the radar, the rotation radius of the target is l5 = 0.5 m, and the rotation frequency is w d5 =80r / s, and the target is v d1 =10m / s radial velocity movement, the target echo signal in the radar, the relationship between distance and time domain is as follows Figure 2 As shown by Figure 1 It can be seen that due to the movement of the target and the rotation of the rotor, the radar echo is a mixed signal of linear frequency modulation caused by the translational motion of the target body and sinusoidal frequency modulation caused by the micro-motion of the target.

[0035] Then, a sliding window with a length of 64 is first used to truncate the echo data sequence x(n), n=1, L, N into an echo sequence group, thereby completing the preprocessing of the echo signal.

[0036] Then through the expression φ R (t) = exp(Φ v t+Φ0) constructs a rotation operator, where φ H is the rotation operator, Φ v is the rotation angle of the echo signal, Φ0 is the initial angle of the echo signal, and t is the time series of the echo signal, so that the echo signal is as follows Figure 3As shown, after a certain angle of rotation, the width of the translation signal energy projected on the range axis reaches the narrowest;

[0037] Scan the echo signal in the vertical direction of the distance axis to obtain the echo signal rotation Φ v The energy distribution after Among them, g σ (t) is a Gaussian window function with a time width of σ. Then calculate

[0038] in, is the analytical signal of the rotated echo signal, S d is the analytical signal of the echo signal, is the complex form of the Gaussian window function with a time width of σ,

[0039] Then through Calculate Figure 4 The parameter space of the echo signal energy in the rotation domain is shown as follows, where is the parameter space of energy in the echo signal, Φ v is the rotation angle of the echo signal, and Φ0 is the initial angle of the echo signal.

[0040] In the rotation domain, the bandwidth of the target translation component reaches the narrowest, which is optimized to the impulse response under ideal conditions, and this component maintains the initial distance of the component along the time axis. The energy of other components is more dispersed due to the mismatch of signal form. At this time, the two components can be significantly distinguished, as shown in the following figure: Figure 4 The parametric search space for the rotation domain signal is shown.

[0041] Finally, the energy of the translational signal in the echo signal is found by searching for the peak value of the signal energy in the parameter search space, thereby compensating for the translational component. In this embodiment, after calculation, the peak value of the echo signal in the parameter space is The energy concentration is the highest and the bandwidth is the narrowest at the point. At this time, the target translation parameters are obtained, and the obtained motion parameters are used to perform motion compensation on the echo signal.

[0042] A detection method for a rotary-wing UAV comprises: obtaining an echo signal sent by a moving target; processing the echo signal using the above-mentioned echo signal processing method to determine whether a corresponding micro-Doppler signal can be obtained, and if so, determining that the moving target is a rotary-wing UAV.

[0043] Figure 5 A schematic diagram showing the comparison of the detection accuracy of the front and rear rotor drones after the translational signal compensation according to an embodiment of the present disclosure;

[0044] When the false alarm probability is set to P fa =10-6 Under different SNR conditions, the detection probability results of the slow UAV before and after phase compensation are compared. Figure 5 As shown in the figure, due to the micro-motion phase compensation, when SNR = -20dB, the detection accuracy of the rotor UAV after compensation is improved by nearly 15% compared with that before compensation.

[0045] Therefore, the method proposed in the present invention can effectively improve the detection performance of the radar system in detecting slow-moving "low, slow and small" targets represented by drones.

[0046] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for processing an echo signal, characterized in that: include: S1, pre-processing echo signals, wherein the echo signals include translational signals generated by the target body movement and micro-Doppler signals generated by the target micro-motion, and the translational signals are linear frequency modulation signals; the pre-processing echo signals in step S1 includes using a sliding window to convert the echo data sequence The interception is the echo sequence group; S2, construct a rotation operator, and after the echo signal is rotated by a predetermined angle according to the rotation operator, the widening of the translation signal energy projected on the range axis reaches the narrowest; the expression of the rotation operator in step S2 is: ,in, is the rotation operator, is the rotation angle of the echo signal, is the initial angle of the echo signal, and t is the time series of the echo signal; S3, scanning the echo signal in the direction perpendicular to the distance axis to obtain the parameter space of the echo signal energy; the corresponding relationship of the parameters in the parameter space of the echo signal energy in step S3 is: ,in, is the analytical signal of the rotated echo signal, is the parameter space of energy in the echo signal, is the rotation angle of the echo signal, is the initial angle of the echo signal, and t is the time series of the echo signal; Said ,in, , is the analytical signal of the echo signal, The time width is The complex form of the Gaussian window function; Said , The time width is Gaussian window function; S4, determining the translation signal according to the peak value of the parameter space and eliminating the translation signal to obtain the micro-Doppler signal.

2. The echo signal processing method according to claim 1, characterized in that: The micro-Doppler signal is a sinusoidal frequency modulation signal.

3. A method for detecting a rotary-wing UAV, characterized in that: include: Acquire an echo signal sent by a moving target; The echo signal is processed using the echo signal processing method as claimed in claim 1 to determine whether a corresponding micro-Doppler signal can be obtained. If so, it is determined that the moving target is a rotary-wing drone.

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