Micro-Doppler signature enhancement method for rotary-wing UAV using dual-station radar

Abstract

The present invention provides a method for enhancing micro-Doppler characteristics of a rotary-wing unmanned aerial vehicle (UAV) using dual-station radars, comprising the following steps: obtaining echo signals of a target to be analyzed from two radars, determining a first radar and a second radar; preprocessing the echo signals of the two radars; estimating a local peak value occurrence period of the echo signal of the first radar; increasing the slow-time sampling rate of the echo signal of the second radar to the same as that of the first radar based on a characteristic of the local peak value period; performing a short-time Fourier transform on the echo signal to obtain a first time-frequency spectrum and a second time-frequency spectrum; performing a Radon transform on the first time-frequency spectrum and the second time-frequency spectrum, processing the Radon transform results in a Radon transform domain, and obtaining a time-frequency spectrum diagram with enhanced micro-Doppler characteristics; when the data transmission volume is limited, the radar with a low slow-time sampling rate can obtain a time-frequency spectrum diagram with enhanced micro-Doppler characteristics of the UAV target; and when the data transmission volume is sufficient, the micro-Doppler characteristics of the UAV target obtained in the time-frequency spectrum diagram are enhanced compared to those obtained directly.

Description

Technical Field

[0001] The present invention relates to the technical field of UAV target radar echo signal processing, and in particular to a method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar. Background Art

[0002] Radar is one of the most commonly used means to detect rotorcraft UAV targets. Micro-Doppler characteristics are important features for distinguishing UAV targets from other targets using radar.

[0003] In the existing technology, domestic and foreign scholars have conducted a series of studies on the enhancement of micro-Doppler characteristics through electromagnetic feature fusion, inverse Radon transform, and time-frequency domain analysis methods. These studies are mainly limited to single-station radars. Due to the limitations of observation angle and radar parameters, the micro-Doppler characteristics reflected in the time-frequency spectrum of the target obtained by a single radar under certain conditions are not significant enough. Summary of the Invention

[0004] The present invention provides a method for enhancing the micro-Doppler signature of a rotary-wing UAV using a dual-station radar, so as to solve the problem in the prior art that the micro-Doppler signature of the UAV target obtained by a single radar is not significant enough.

[0005] To achieve the above object, the present invention provides the following technical solution, comprising the steps of:

[0006] A method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar, characterized by comprising the steps of:

[0007] Acquire echo signals of the same target to be analyzed from two radars respectively; and determine a first radar and a second radar; wherein determining the first radar includes:

[0008] determining the radar with a high slow-time sampling rate as the first radar;

[0009] If the slow-time sampling rates of the two radars are the same, one of them is randomly selected as the first radar;

[0010] preprocessing the first radar echo signal and the second radar echo signal;

[0011] estimating a local peak value occurrence period of the first radar echo signal based on the preprocessed first radar echo signal to obtain a local peak value period feature;

[0012] increasing the slow-time sampling rate of the preprocessed second radar echo signal to the same as the slow-time sampling rate of the first radar echo signal according to the local peak value period feature;

[0013] Performing a short-time Fourier transform on the preprocessed first radar echo signal to obtain a first time-frequency spectrum; performing a short-time Fourier transform on the preprocessed second radar echo signal with the slow-time sampling rate increased to obtain a second time-frequency spectrum;

[0014] Performing Radon transform on the first time-frequency spectrum to obtain a first Radon transform result; performing Radon transform on the second time-frequency spectrum to obtain a second Radon transform result;

[0015] Processing the first Radon transform result and the second Radon transform result in a Radon transform domain to obtain a time-frequency spectrum diagram with enhanced micro-Doppler characteristics of the target to be analyzed;

[0016] Processing the first Radon transform result and the second Radon transform result in a Radon transform domain includes:

[0017] performing time alignment on the first Radon transform result and the second Radon transform result in the Radon transform domain;

[0018] fusing the time-aligned first Radon transform result and the second Radon transform result in the Radon transform domain to obtain a Radon transform result;

[0019] Performing filtering on the fused Radon transform results in the Radon transform domain;

[0020] Perform an inverse Radon transform on the filtered Radon transform result.

[0021] Preferably, in an embodiment of the present invention, the preprocessing includes:

[0022] Remove clutter from echo signals;

[0023] The spectrum of the echo signal after removing the ground clutter is shifted in the frequency direction, and the peak of the shifted spectrum is moved to zero frequency.

[0024] Preferably, in an embodiment of the present invention, estimating the occurrence period of a local peak value of the first radar echo signal includes:

[0025] Extracting the maximum amplitude point of the time domain waveform of the first radar echo signal;

[0026] The maximum amplitude point of the time domain waveform whose relative height difference of the peak value is greater than a specified threshold is selected as the candidate peak value; the relative height difference of the peak value is the difference between the maximum amplitude point of the time domain waveform and the larger valley point of the valley points on both sides; the specified threshold is a value between 0 and the maximum amplitude value;

[0027] Calculating the time intervals between adjacent candidate peak values; and first calculating the mean m1 and standard deviation σ1 of each time interval;

[0028] The occurrence time t of each candidate peak value i , i=1,2,… is the center, if t i The candidate peak value at the time is not the time interval [t i -m1 / 2,t i +m1 / 2], removing the candidate peak value;

[0029] Calculate the time intervals between adjacent candidate peak values ​​for the second time using the remaining candidate peak values; and calculate the mean m2 and standard deviation σ2 of each time interval;

[0030] After removing the time intervals that are not within the interval [m2-σ2, m2+2], the mean m3 and standard deviation σ3 of the remaining time intervals are calculated for the third time, and the mean m3 is used as the local peak value occurrence period of the first radar echo signal.

[0031] Preferably, in an embodiment of the present invention, the step of selecting the maximum amplitude point of the time domain waveform whose relative height difference of the peak value is greater than a specified threshold as the candidate peak value comprises:

[0032] The maximum value of all the time domain waveform amplitude maximum points is defined as P max , in the threshold interval [0,P max ] range, calculate the number of the maximum amplitude points of the time domain waveform with the relative height difference of the peak value greater than the threshold value when taking different thresholds at intervals of 0.5, and use the threshold values ​​T1, T2, ..., T1 arranged from small to large to obtain the maximum value of the time domain waveform. R , and we get p1, p2, …, p respectively. R a maximum amplitude point of the time domain waveform;

[0033] In the p1,p2,…,p R In the sequence, select the one that satisfies the condition p r ≥3,p r-1 -p r ≤3, r=2, 3, ..., the longest subsequence of R, the median value p of the longest subsequence M The corresponding threshold T M is the specified threshold for the relative height difference of the peak;

[0034] Select the peak whose relative height difference is greater than the specified threshold T M The maximum amplitude point of the time domain waveform is the candidate peak value.

[0035] Preferably, in an embodiment of the present invention, increasing the slow-time sampling rate of the preprocessed second radar echo signal to the same as the slow-time sampling rate of the first radar echo signal according to the local peak value period feature includes:

[0036] Define the slow time sampling interval of the first radar as Δt, each slow time sampling moment of the first radar as nΔt, n=0, 1, 2, ..., and the occurrence period of the local peak value of the first radar as T;

[0037] Within the first cycle time [0, T], estimating the reconstructed value of the second radar echo signal after upsampling at time nΔt, n=0, 1, 2, ...;

[0038] The reconstructed signal of the second radar after upsampling within the first cycle time [0, T] is periodically extended to obtain an upsampled signal with the same duration and the same slow time sampling interval as the first radar.

[0039] Preferably, in an embodiment of the present invention, estimating the reconstructed value of the second radar echo signal after upsampling at time nΔt, n=0, 1, 2, ... within the first cycle time [0, T[, includes:

[0040] For the kth time instant kΔt after upsampling, calculate the time value kΔt+mT within the duration of the second radar echo signal, where m=0, 1, 2, ..., M-1; and use the sampling value of the sampling time instant with the smallest time difference from kΔt+mT in the second radar echo signal as the sampling value at the kth time instant kΔt after upsampling by the second radar.

[0041] Preferably, in an embodiment of the present invention, the step of time-aligning the first Radon transform result and the second Radon transform result in the Radon transform domain includes:

[0042] The section data corresponding to the transformation angle of 0 degrees extracted from the first Radon transform result is defined as the first section data; the section data corresponding to the transformation angle of 0 degrees extracted from the second Radon transform result is defined as the second section data; the first section data and the second section data use time as the independent variable; the intensity values ​​of the first Radon transform result and the second Radon transform result are the dependent variables;

[0043] According to the occurrence period T of the local peak value of the first radar, within the offset time range of (-T / 2, T / 2), the correlation function between the first profile data and the second profile data when the first profile data is offset at different times is calculated; and according to the time offset of the first profile data corresponding to the maximum correlation function, the first Radon transform result is offset by the same time to achieve temporal alignment of the first Radon transform result and the second Radon transform result.

[0044] Preferably, in an embodiment of the present invention, fusing the time-aligned first Radon transform result and the second Radon transform result in the Radon transform domain includes:

[0045] The first Radon transform result and the second Radon transform result are fused by adding corresponding positions in the Radon transform domain.

[0046] Preferably, in an embodiment of the present invention, filtering the fused Radon transform result in the Radon transform domain includes:

[0047] The filtering process in which the gain monotonically decreases from an angle of 0 to 90 degrees and monotonically increases from an angle of 90 to 180 degrees in the Radon transform domain is achieved by the filter.

[0048] Preferably, in an embodiment of the present invention, the filter includes the following formula:

[0049]

[0050] In the formula, H(θ) is the system function of the filter, α is the filter characteristic coefficient, and θ is the angle corresponding to the Radon transform result.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] The present invention provides a method for enhancing the micro-Doppler signature of a rotary-wing UAV using dual-station radars. When the amount of data transmitted between the two radars is limited, the method can transmit only the occurrence period of the local peak value of the echo signal of the target to be analyzed, estimated by the radar with a high slow-time sampling rate, so that the radar with a low slow-time sampling rate can obtain a time-frequency spectrum with enhanced micro-Doppler signature of the UAV target. When the amount of data transmitted between the two radars is sufficient, a time-frequency spectrum can be obtained after the data of the two radars are fused. The micro-Doppler signature of the UAV target in the fused time-frequency spectrum is enhanced compared to that obtained directly from the two radars.

[0053] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and to implement it according to the contents of the specification, and to make the above and other purposes, technical features and advantages of the present invention easier to understand, one or more preferred embodiments are listed below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0055] Figure 1 This is a step diagram of a method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar according to an embodiment of the present invention;

[0056] Figure 2 Schematic diagram of the system function of the filter according to an embodiment of the present invention;

[0057] Figure 3 Schematic diagram showing a comparison of a radar echo signal with a slow time and low sampling rate before and after upsampling according to an embodiment of the present invention;

[0058] Figure 4 This is a time-frequency spectrum diagram corresponding to the echo signal of the slow-time low sampling rate radar before and after upsampling according to an embodiment of the present invention;

[0059] Figure 5 This is a schematic diagram of the Radon transform result of the second time-frequency spectrum according to an embodiment of the present invention;

[0060] Figure 6 This is the time-frequency spectrum directly obtained by the first radar and the second radar and the fused time-frequency spectrum in the embodiment of the present invention. DETAILED DESCRIPTION

[0061] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

[0062] Unless expressly stated otherwise, throughout the specification and claims, the term “comprise” or variations such as “include” or “comprising” will be understood to include the stated elements or components but not to exclude other elements or components.

[0063] In this document, the terms "first", "second", etc. are used to distinguish two different elements or parts, and are not used to limit specific positions or relative relationships. In other words, in some embodiments, the terms "first", "second", etc. can also be interchangeable with each other.

[0064] The following combination Figures 1 to 6 , describing embodiments of the present invention.

[0065] In the existing technology, due to the limitations of observation angle and radar parameters, the micro-Doppler characteristics of the target obtained by a single radar under some conditions are not significant enough. To solve this problem, Figure 1 As shown, in an embodiment of the present invention, a method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar is provided, comprising the steps of:

[0066] S101, respectively obtaining echo signals of the same target to be analyzed from two radars; and determining a first radar and a second radar; wherein determining the first radar includes:

[0067] determining the radar with a high slow-time sampling rate as the first radar;

[0068] If the slow-time sampling rates of the two radars are the same, one of them is randomly selected as the first radar;

[0069] In an embodiment of the present invention, the radar with the higher slow-time sampling rate of the two radars is determined as the first radar. If the two radars have the same slow-time sampling rate, one radar is arbitrarily determined as the first radar and the other radar is determined as the second radar. The slow-time sampling rate is: for a pulse radar, it refers to the pulse repetition frequency; for a linear frequency modulated continuous wave radar, it refers to the inverse of the modulation period.

[0070] S103: preprocessing the first radar echo signal and the second radar echo signal;

[0071] In the practice of the present invention, pretreatment includes:

[0072] Remove clutter from echo signals;

[0073] The spectrum of the echo signal after removing the ground clutter is shifted in the frequency direction, and the peak of the shifted spectrum is moved to zero frequency.

[0074] Specifically, the ground clutter component is removed and the spectrum of the echo signal with a Doppler frequency f less than a certain threshold is set to zero to achieve the purpose of suppressing ground clutter, as shown in the following formula:

[0075] F(f)=0,|f|<f0 Formula (1)

[0076] In formula (1), F(f) is the spectrum obtained after Fourier transform of the echo signal; f0 is the threshold for setting the spectrum to zero; the threshold can be 2 / λ, where λ is the carrier frequency of the radar echo signal.

[0077] Usually, in the echo signal, the energy of the drone body is greater than that of the blades. Therefore, by finding the spectrum peak of the echo signal after removing the ground clutter component, the target body frequency is estimated for the echo signal after removing the ground clutter component, and the target body Doppler frequency is compensated to zero frequency, as shown in the following formula:

[0078]

[0079] In formula (2), F'(f) is the spectrum of the echo signal after removing the ground clutter; argmax(·) is the frequency f corresponding to the maximum value of the spectrum modulus; the spectrum is shifted along the frequency direction Shifts the spectrum peak to zero frequency.

[0080] S105: estimating a local peak value occurrence period of the first radar echo signal based on the preprocessed first radar echo signal to obtain a local peak value period feature;

[0081] In the embodiment of the present invention, estimating the occurrence period of a local peak value of the first radar echo signal includes:

[0082] Extracting the maximum amplitude point of the time domain waveform of the first radar echo signal;

[0083] The peak relative height difference is the difference between the maximum amplitude point of the time domain waveform and the larger valley point on both sides. The specified threshold is a value between 0 and the maximum amplitude point of the time domain waveform.

[0084] Calculate the time intervals between adjacent candidate spike values; and first calculate the mean m1 and standard deviation σ1 of each time interval;

[0085] Take the time t at which each candidate peak value appears i , i=1,2,… is the center, if t i The candidate peak value at the moment is not the time interval [t i m1 / 2,t i +m1 / 2], then remove the alternative peak value;

[0086] Calculate the time intervals between adjacent candidate spike values ​​for the second time using the remaining candidate spike values; and calculate the mean m2 and standard deviation σ2 of each time interval;

[0087] After removing the time intervals not within the interval [m2-σ2, m2+σ2], the mean m3 and standard deviation σ3 of the remaining time intervals are calculated for the third time, and the mean m3 is used as the local peak value occurrence period of the first radar echo signal.

[0088] In the embodiment of the present invention, the time domain waveform amplitude maximum point refers to the local maximum value of the time domain waveform amplitude of the echo signal.

[0089] Furthermore, in an embodiment of the present invention, selecting a time domain waveform amplitude maximum point with a peak relative height difference greater than a specified threshold as a candidate peak value includes:

[0090] Define the maximum value of all time domain waveform amplitude maximum points as P max , in the threshold interval [0,P max ] range, the number of time domain waveform amplitude maximum value points with the peak relative height difference greater than the threshold value obtained when taking different thresholds is calculated with an interval of 0.5, and the number of time domain waveform amplitude maximum value points with the peak relative height difference greater than the threshold value is calculated by R thresholds T1, T2, ..., T arranged from small to large. R , and we get p1, p2, …, p respectively. R The maximum amplitude point of the time domain waveform;

[0091] In p1, p2, ..., p R In the sequence, select the one that satisfies the condition p r ≥3,p r-1 -p r ≤3,r=2,3,…,R, the longest subsequence, the median value p of the longest subsequence M The corresponding threshold T M is the specified threshold for the relative height difference of the peak;

[0092] Select the peak whose relative height difference is greater than the specified threshold T M The maximum amplitude point of the time domain waveform is the candidate peak value.

[0093] S107: increasing the slow-time sampling rate of the preprocessed second radar echo signal to the same as the slow-time sampling rate of the first radar echo signal according to the local peak value period characteristic;

[0094] In the embodiment of the present invention, the slow time sampling interval of the first radar is defined as Δt, the slow time sampling moments of the first radar are nΔt, n0, 1, 2, ..., and the occurrence period of the local peak value of the first radar is T;

[0095] Within the first cycle time [0, T], estimate the reconstructed value of the second radar echo signal after upsampling at time nΔt, n = 0, 1, 2, ...;

[0096] The reconstructed signal after upsampling by the second radar in the first cycle time range [0, T is periodically extended to obtain an upsampled signal with the same duration and slow time sampling interval as the first radar.

[0097] Furthermore, in an embodiment of the present invention, within the first cycle time [0, T], estimating the reconstructed value of the second radar echo signal after upsampling at time nΔt, n=0, 1, 2, ... includes:

[0098] For the kth time instant kΔt after upsampling, calculate the time value kΔt+mT within the duration of the second radar echo signal, where m=0, 1, 2, ..., M1. In the second radar echo signal, use the sampling value at the sampling instant with the smallest time difference from kΔt+mT as the sampling value at the kth time instant kΔt after upsampling by the second radar.

[0099] S109: performing a short-time Fourier transform on the preprocessed first radar echo signal to obtain a first time-frequency spectrum; performing a short-time Fourier transform on the preprocessed second radar echo signal with the slow-time sampling rate increased to obtain a second time-frequency spectrum;

[0100] In the embodiment of the present invention, short-time Fourier transform is performed on the preprocessed first radar echo signal and the preprocessed second radar echo signal with the slow time sampling rate increased, thereby obtaining a first time-frequency spectrum and a second time-frequency spectrum.

[0101] S111, performing Radon transform on the first time-frequency spectrum to obtain a first Radon transform result; performing Radon transform on the second time-frequency spectrum to obtain a second Radon transform result;

[0102] In the embodiment of the present invention, the micro-Doppler characteristics of the blade time-frequency flicker presented in the time-spectrum diagrams of the first time-spectrum and the second time-spectrum are rectangular flickers perpendicular to the time axis that appear within a certain frequency band. Utilizing this characteristic, the Radon transform is used to map the blade time-frequency flicker to peak points. The Radon transform is defined as follows:

[0103] R(θ,r)=∫∫f(x,y)δ(xcosθ+ysinθ-r)dxdy Formula (3)

[0104] In formula (3), f(x, y) is the image to be transformed; x, y are the two-dimensional coordinates of the image to be transformed, that is, the frequency and time of the time-spectrogram respectively; θ is the angle of the line along which the integration is performed in the Radon transform relative to the vertical upward direction of the time-spectrogram; r is the distance from the line along which the integration is performed in the Radon transform to the center of the time-spectrogram; δ(τ) is the Dirac function, which satisfies δ(τ) = 0 when τ ≠ 0 and R(θ,r) is the result of Radon transform.

[0105] S113, processing the first Radon transform result and the second Radon transform result in a Radon transform domain to obtain a time-frequency spectrum diagram with enhanced micro-Doppler characteristics of the target to be analyzed;

[0106] Processing the first Radon transform result and the second Radon transform result in a Radon transform domain includes:

[0107] performing time alignment on the first Radon transform result and the second Radon transform result in the Radon transform domain;

[0108] fusing the time-aligned first Radon transform result and the second Radon transform result in the Radon transform domain to obtain a Radon transform result;

[0109] Performing filtering on the fused Radon transform results in the Radon transform domain;

[0110] Perform an inverse Radon transform on the filtered Radon transform result.

[0111] In the embodiment of the present invention, time alignment of the first Radon transform result and the second Radon transform result is performed in the Radon transform domain, including:

[0112] The section data corresponding to the transformation angle of 0 degrees extracted from the first Radon transform result is defined as the first section data; the section data corresponding to the transformation angle of 0 degrees extracted from the second Radon transform result is defined as the second section data; the first section data and the second section data use time as the independent variable; the intensity value of the first Radon transform result and the second Radon transform result is the dependent variable;

[0113] According to the occurrence period T of the local peak value of the first radar, within the offset time range of (-T / 2, T / 2), the correlation function between the first profile data and the second profile data when the first profile data is offset at different times is calculated; and according to the time offset of the first profile data corresponding to the maximum correlation function, the first Radon transform result is offset by the same time to achieve temporal alignment of the first Radon transform result and the second Radon transform result.

[0114] The first Radon transform result and the second Radon transform result after time alignment are fused in the Radon transform domain, including:

[0115] The first Radon transform result and the second Radon transform result are fused by adding corresponding positions in the Radon transform domain.

[0116] Performing filtering processing on the fused Radon transform result in the Radon transform domain, including:

[0117] The filtering process in which the gain monotonically decreases from an angle of 0 to 90 degrees and monotonically increases from an angle of 90 to 180 degrees in the Radon transform domain is achieved by the filter.

[0118] Among them, the filter includes the following formula:

[0119]

[0120] In formula (4), H(θ) is the system function of the filter, α is the filter characteristic coefficient, and θ is the angle corresponding to the Radon transform result; the system function of the filter is as follows: Figure 2 shown.

[0121] In practical applications, the filter characteristic coefficient α can be set to 10, so that the parts of the Radon transform result far away from the angles of 0 degrees and 180 degrees are well suppressed.

[0122] In the embodiment of the present invention, the filtered Radon transform result is subjected to an inverse Radon transform using the following formula:

[0123] p(θ,ω)=∫R f (θ,r)e -jωr dr Formula (5)

[0124]

[0125] In formula (5), R f (θ, r) is the filtered Radon transform result to be inverse Radon transform; θ is the angle of the line along which the integration is performed in the Radon transform relative to the vertical upward direction of the time-spectrogram; r is the distance from the line along which the integration is performed in the Radon transform to the center of the time-spectrogram; ω is the spatial frequency.

[0126] In formula (6), f o (x, y) is the time-spectrum diagram after inverse Radon transform, and x, y are the frequency and time of the corresponding time-spectrum diagram.

[0127] The following is a detailed experiment to illustrate that the present invention can obtain a time-frequency spectrum diagram with enhanced micro-Doppler characteristics of a UAV target.

[0128] The experiment was conducted using simulated drone radar echo signals. Both the first and second radars are pulse systems. The pulse repetition frequency of the first radar with a high slow-time sampling rate is 8 times that of the second radar, which is 16666.67Hz. The signal-to-noise ratio of the rotor and noise of the drone target echo signal of the first radar is set to 0dB, and the signal-to-noise ratio of the rotor and noise of the drone target echo signal of the second radar is set to 5dB.

[0129] like Figure 3 The comparison of the results before and after upsampling of the simulated UAV echo signal of the second radar with a slow time sampling rate is shown. Figure 3 Figure a shows the echo signal before upsampling, and Figure b shows the echo signal after upsampling. Figure a cannot well reflect the periodic spike characteristics caused by the rotation of the UAV rotor due to the insufficient slow-time sampling rate. Figure b better restores the periodic spike characteristics caused by the rotation of the UAV rotor.

[0130] like Figure 4 This is the time-frequency spectrum of the simulated UAV echo signal before and after upsampling of the second radar with a low slow time sampling rate. The time-frequency spectrum is obtained by short-time Fourier transform. Figure 4 Figure a is the time-frequency spectrum of the echo signal before upsampling, and Figure b is the time-frequency spectrum of the echo signal after upsampling; due to the low slow-time sampling rate in Figure a, the time-frequency spectrum has a certain folding phenomenon, and the periodic vertical lines in the time-frequency spectrum are the time-frequency flickers corresponding to the UAV rotor. It is difficult to distinguish the end points of the vertical lines in the figure, and it is difficult to distinguish the maximum Doppler frequency corresponding to the UAV rotor through the time-frequency flicker, and the time-frequency flicker is relatively weak; Figure b is the local peak value occurrence period of the target echo signal to be analyzed with a very small amount of transmission data estimated by the first radar. After the upsampling processing using the local peak value period feature of the echo signal provided by the present invention, the time-frequency spectrum is obtained. It can be seen that the time-frequency flicker in the time-frequency spectrum of Figure b, that is, the periodic vertical lines are clearer, and it is also easy to obtain the maximum Doppler frequency of the time-frequency flicker, and the micro-Doppler feature of Figure b is significantly enhanced compared to that of Figure a.

[0131] Figure 5 is the Radon transform result of the second time spectrum, that is Figure 4 The result of Radon transformation in Figure b shows that the changed energy is mainly concentrated near the angles of 0 and 180 degrees. In particular, there are significant periodic bright spots on the 0 and 180 degree lines. These periodic bright spots correspond to the time-frequency flicker in the time-frequency spectrum, that is, the vertical lines in the time-frequency spectrum.

[0132] Figure 6 Comparison between the time-spectrum diagram directly obtained by the first radar and the second radar and the fused time-spectrum diagram; Figure 6Figure (a) shows the time-frequency spectrum of the drone's return signal from the second radar (with a lower slow-time sampling rate) using a short-time Fourier transform. Figure (b) shows the time-frequency spectrum of the drone's return signal from the first radar (with a higher slow-time sampling rate) using a short-time Fourier transform. Figure (c) shows the final time-frequency spectrum obtained through fusion enhancement. It can be seen that the time-frequency flicker in Figure (c), the periodic vertical lines that characterize the drone's micro-Doppler signature, is clearer than in the other two figures, enhancing the micro-Doppler signature. Furthermore, the time-frequency spectrum of the fuselage, which is not a micro-Doppler signature, and the horizontal lines in the time-frequency spectrum, has also been effectively removed.

[0133] Quantitative evaluation of time-frequency flicker contrast using Figure 6 The enhancement effect of the micro-Doppler feature of the time-frequency spectrum after fusion enhancement, the time-frequency flicker contrast is the ratio of the average power of the time-frequency flicker part in the time-frequency spectrum to the average power of the noise, that is:

[0134]

[0135] In formula (7), C is the time-frequency flicker contrast; P flash is the average power of the time-frequency flicker part; P noise is the average power of the noise.

[0136] The average power of the time-frequency flicker is calculated as follows: for each time-frequency flicker, the mean square value of the main frequency part of the time-frequency flicker at the time-frequency flicker moment in the time-frequency spectrum is calculated, and then the average of all the mean square values ​​of the time-frequency flicker is taken as the average power of the time-frequency flicker. The specific calculation formula is as follows:

[0137]

[0138] In formula (8), [f min ,f max ] is the frequency range of the time-frequency flicker in the selected time-spectrum diagram; N is the number of samples in the frequency range; M is the number of flickers; STFT(t i ,f j ) is the time-frequency spectrum result obtained by short-time Fourier transform.

[0139] In order to reduce the impact of interference, the flickering time is within the range of 20% to 80%, and the flickering frequency range is 10% to 20% of PRF / 2, where PRF is the radar pulse repetition frequency.

[0140] The average power of the noise is calculated as follows: a specific frequency range with relatively high frequencies that does not contain micro-Doppler characteristics is selected as the noise frequency range. The average mean square value of the spectrum within this frequency range is calculated as the average power of the noise. The specific calculation formula is as follows:

[0141]

[0142] In formula (9), [f' min ,f' max ] is the frequency range of the noise in the selected time-spectrum; U is the number of samples in the frequency range; L is the number of time sampling points in the time range for calculating the noise power.

[0143] To reduce the impact of interference, the noise in the range of 20% to 80% of the time length is taken, and the noise frequency range is 50% to 100% of PRF / 2, where PRF is the radar pulse repetition frequency.

[0144] Table 1 below shows the comparison of the time-frequency scintillation contrast of the two radar time-spectrum diagrams before and after fusion; the time-spectrum diagram of the second radar echo signal before upsampling is Figure 6 In Figure a, the time-frequency spectrum of the first radar echo signal is Figure 6 In the middle b figure, the fused time-frequency spectrum is Figure 6 In Figure c, when the data transmission capacity is large enough, the fusion of the subsequent steps of this application can be carried out. From the quantitative comparison in Table 1, it can be further seen that the micro-Doppler characteristics of the time-spectrum graph after fusion enhancement are better than the micro-Doppler characteristics of the time-spectrum graph obtained by a single radar alone, and the micro-Doppler characteristics of the time-spectrum graph after fusion are enhanced.

[0145] Table 1:

[0146]

[0147] In summary, the method for enhancing the micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar provided in an embodiment of the present invention can, when the amount of data transmission between the two radars is limited, only transmit the local peak occurrence period of the target echo signal to be analyzed, estimated by the radar with a high slow-time sampling rate, so that the radar with a low slow-time sampling rate can obtain a time-frequency spectrum with enhanced micro-Doppler characteristics of the UAV target. When the amount of data transmission between the two radars is sufficient, a time-frequency spectrum can be obtained after the data of the two radars are fused. The micro-Doppler characteristics of the UAV target in the fused time-frequency spectrum are enhanced compared to those directly obtained from the two radars.

Claims

1. A method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar, characterized in that: Including steps: Obtain the echo signals of the same target to be analyzed from two radars respectively; and determining a first radar and a second radar; wherein determining the first radar includes: determining the radar with a high slow-time sampling rate as the first radar; If the slow-time sampling rates of the two radars are the same, one of them is randomly selected as the first radar; preprocessing the first radar echo signal and the second radar echo signal; estimating a local peak value occurrence period of the first radar echo signal based on the preprocessed first radar echo signal to obtain a local peak value period feature; According to the local peak value period feature, increasing the slow time sampling rate of the preprocessed second radar echo signal to the same as the slow time sampling rate of the first radar echo signal; Performing a short-time Fourier transform on the preprocessed first radar echo signal to obtain a first time-frequency spectrum; performing a short-time Fourier transform on the preprocessed second radar echo signal with the slow-time sampling rate increased to obtain a second time-frequency spectrum; Performing Radon transform on the first time-frequency spectrum to obtain a first Radon transform result; performing Radon transform on the second time-frequency spectrum to obtain a second Radon transform result; Processing the first Radon transform result and the second Radon transform result in a Radon transform domain to obtain a time-frequency spectrum diagram with enhanced micro-Doppler characteristics of the target to be analyzed; Processing the first Radon transform result and the second Radon transform result in a Radon transform domain includes: Time-aligning the first Radon transform result and the second Radon transform result in the Radon transform domain; fusing the time-aligned first Radon transform result and the second Radon transform result in the Radon transform domain to obtain a Radon transform result; Performing filtering on the fused Radon transform results in the Radon transform domain; Perform an inverse Radon transform on the filtered Radon transform result.

2. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar according to claim 1, characterized in that: The preprocessing comprises: Remove clutter from echo signals; The spectrum of the echo signal after removing the ground clutter is shifted in the frequency direction, and the peak of the shifted spectrum is moved to zero frequency.

3. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a bistatic radar according to claim 1, characterized in that: The estimating a local peak value occurrence period of the first radar echo signal includes: Extracting the maximum amplitude point of the time domain waveform of the first radar echo signal; The maximum amplitude point of the time domain waveform whose relative height difference of the peak value is greater than a specified threshold is selected as the candidate peak value; the relative height difference of the peak value is the difference between the maximum amplitude point of the time domain waveform and the larger valley point on both sides; the specified threshold is a value between 0 and the maximum amplitude of the time domain waveform; Calculating the time intervals between adjacent candidate peak values; and first calculating the mean m1 and standard deviation σ1 of each time interval; The occurrence time t of each candidate peak value i , i=1,2,… is the center, if t i The candidate peak value at the time is not the time interval [t i -m1 / 2,t i +m1 / 2], removing the candidate peak value; Calculate the time intervals between adjacent candidate peak values ​​for the second time using the remaining candidate peak values; and calculate the mean m2 and standard deviation σ2 of each time interval; After removing the time intervals that are not within the interval [m2-σ2, m2+σ2], the mean m3 and standard deviation σ3 of the remaining time intervals are calculated for the third time, and the mean m3 is used as the local peak value occurrence period of the first radar echo signal.

4. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar according to claim 3, characterized in that: The step of selecting the maximum amplitude point of the time domain waveform whose relative height difference of the peak value is greater than a specified threshold as the candidate peak value comprises: The maximum value of all the time domain waveform amplitude maximum points is defined as P max , in the threshold interval [0,P max ] range, the number of the maximum amplitude points of the time domain waveform whose relative height difference of the peak value obtained when taking different thresholds is greater than the threshold is calculated at intervals of 0.5, and the threshold values ​​T1, T2, ..., T R , and we get p1, p2, …, p respectively. R a maximum amplitude point of the time domain waveform; In the p1,p2,…,p R In the sequence, select the one that satisfies the condition p r ≥3,p r-1 -p r ≤3, r=2,3,…,R, the longest subsequence, the median value p of the longest subsequence M The corresponding threshold T M is the specified threshold for the relative height difference of the peak; Select the peak whose relative height difference is greater than the specified threshold T M The maximum amplitude point of the time domain waveform is the candidate peak value.

5. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar according to claim 1, characterized in that: Increasing the slow-time sampling rate of the preprocessed second radar echo signal to the same as the slow-time sampling rate of the first radar echo signal according to the local peak value period feature, including: Define the slow time sampling interval of the first radar as Δt, each slow time sampling moment of the first radar as nΔt, n=0, 1, 2, ..., and the occurrence period of the local peak value of the first radar as T; Within the first cycle time [0, T], estimating the reconstructed value of the second radar echo signal after upsampling at time nΔt, n=0, 1, 2, ...; The reconstructed signal of the second radar after upsampling within the first cycle time [0, T] is periodically extended to obtain an upsampled signal with the same duration and the same slow time sampling interval as the first radar.

6. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar according to claim 5, characterized in that: The estimating, within the first cycle time [0, T], a reconstructed value of the second radar echo signal after upsampling at time nΔt, n=0, 1, 2, ..., includes: For the kth time instant kΔt after upsampling, calculate the time value kΔt+mT within the duration of the second radar echo signal, where m=0, 1, 2, ..., M-1; in the second radar echo signal, use the sampling value of the sampling time instant with the smallest time difference from kΔtmT as the sampling value at the kth time instant kΔt after upsampling by the second radar.

7. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a bistatic radar according to claim 1, characterized in that: The performing time alignment on the first Radon transform result and the second Radon transform result in the Radon transform domain includes: The section data corresponding to the transformation angle of 0 degrees extracted from the first Radon transform result is defined as the first section data; the section data corresponding to the transformation angle of 0 degrees extracted from the second Radon transform result is defined as the second section data; the first section data and the second section data use time as the independent variable; the intensity values ​​of the first Radon transform result and the second Radon transform result are the dependent variables; According to the occurrence period T of the local peak value of the first radar, within the offset time range of (-T / 2, T / 2), the correlation function between the first profile data and the second profile data when the first profile data is offset at different times is calculated; and according to the time offset of the first profile data corresponding to the maximum correlation function, the first Radon transform result is offset by the same time to achieve temporal alignment of the first Radon transform result and the second Radon transform result.

8. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar according to claim 1, characterized in that: Fusing the time-aligned first Radon transform result and the second Radon transform result in the Radon transform domain, including: The first Radon transform result and the second Radon transform result are fused by adding corresponding positions in the Radon transform domain.

9. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a bistatic radar according to claim 1, characterized in that: Performing filtering processing on the fused Radon transform result in the Radon transform domain, including: The filtering process in which the gain monotonically decreases from an angle of 0 to 90 degrees and monotonically increases from an angle of 90 to 180 degrees in the Radon transform domain is achieved by the filter.

10. The method for enhancing micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar according to claim 9, characterized in that: The filter includes the following formula: In the formula, H(θ) is the system function of the filter, α is the filter characteristic coefficient, and θ is the angle corresponding to the Radon transform result.

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