Rotor unmanned aerial vehicle micro-Doppler feature enhancement method using double-station radar

Abstract

The invention provides a rotor unmanned aerial vehicle micro-Doppler feature enhancement method using double-station radars, and the method comprises the steps: obtaining the echo signals of the same to-be-analyzed target of the two radars, and determining a first radar and a second radar; preprocessing the two radar echo signals; estimating a local peak value occurrence period of the first radar echo signal; increasing the slow time sampling rate of the second radar echo signal to be the same as that of the first radar according to the local peak value periodic characteristics; performing short-time Fourier transform on the echo signal to obtain a first time-frequency spectrum and a second time-frequency spectrum; performing Radon transformation on the first time-frequency spectrum and the second time-frequency spectrum, and processing a Radon transformation result in a Radon transformation domain to obtain a micro-Doppler feature enhanced time-frequency spectrogram; when the data transmission quantity is limited, the radar with the slow time sampling rate can obtain a time-frequency spectrogram with enhanced micro-Doppler features of the unmanned aerial vehicle target; when the data transmission quantity is sufficient, the obtained time-frequency spectrogram unmanned aerial vehicle target micro-Doppler characteristics are enhanced compared with directly obtained unmanned aerial vehicle target micro-Doppler characteristics.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle target radar echo signal processing, and in particular to a method for enhancing micro-Doppler characteristics of a rotary-wing unmanned aerial vehicle 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, for the enhancement of micro-Doppler features, domestic and foreign scholars have carried out a series of research 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 features reflected in the time-frequency spectrum of the target obtained by a single radar under some conditions are not significant enough. Summary of the invention

[0004] The present invention provides a method for enhancing micro-Doppler characteristics of a rotary-wing UAV by using a dual-station radar, so as to solve the problem that the micro-Doppler characteristics of a UAV target obtained by a single radar in the prior art are 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 in that it comprises the following steps:

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

[0008] Determine 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 through the preprocessed first radar echo signal to obtain a local peak value period feature;

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

[0013] Performing short-time Fourier transform on the preprocessed first radar echo signal to obtain a first time-frequency spectrum; performing 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 transformation on the first time-frequency spectrum to obtain a first Radon transformation result; performing Radon transformation on the second time-frequency spectrum to obtain a second Radon transformation 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 of the target to be analyzed with enhanced micro-Doppler characteristics;

[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 first Radon transform result and the second Radon transform result after time alignment in the Radon transform domain to obtain a Radon transform result;

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

[0020] An inverse Radon transform is performed 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 ground clutter is translated in the frequency direction, and the peak of the translated spectrum is moved to zero frequency.

[0024] Preferably, in the embodiment of the present invention, the estimating the local peak value occurrence period 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 time domain waveform amplitude maximum value point whose peak relative height difference is greater than a specified threshold is selected as the candidate peak value; the peak relative height difference is the difference between the time domain waveform amplitude maximum value point 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] Calculate the time intervals between adjacent candidate peak values; and calculate the mean m1 and standard deviation σ1 of each time interval for the first time;

[0028] The candidate peak value occurrence time t i , i=1,2,… is the center, if t i The candidate peak value at 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 the 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 time domain waveform amplitude maximum value point whose relative height difference of the peak value is greater than a specified threshold as a candidate peak value includes:

[0032] Define the maximum value of all the time domain waveform amplitude maximum points as P max , in the threshold interval [0,P max ], the number of the maximum value points of the time domain waveform amplitude 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 value point of the time domain waveform amplitude;

[0033] In the p1,p2,…,p R In the sequence, select the 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 value point of the time domain waveform amplitude is the candidate peak value.

[0035] Preferably, in an embodiment of the present invention, according to the local peak value periodicity 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 comprises:

[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, the 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 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 with the smallest time difference with kΔt+mT as the sampling value of the kth time kΔt after upsampling of 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 degree extracted from the first Radon transform result is defined as the first section data; the section data corresponding to the transformation angle of 0 degree extracted from the second Radon transform result is defined as the second section data; the first section data and the second section data take time as the independent variable; the intensity value of the first Radon transform result and the second Radon transform result is the dependent variable;

[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 of the first profile data with the second profile data when 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 time alignment of the first Radon transform result and the second Radon transform result.

[0044] Preferably, in an embodiment of the present invention, fusing the first Radon transform result and the second Radon transform result after time alignment 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 comprises 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 characteristics of a rotary-wing UAV using dual-station radars. When the amount of data transmission between the two radars 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 by transmitting 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. When the amount of data transmission between the two radars is sufficient, a time-frequency spectrum diagram after fusion of the two radar data can be obtained, and the micro-Doppler characteristics of the UAV target in the fused time-frequency spectrum diagram are enhanced compared with those directly obtained 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 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 the accompanying drawings as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the embodiments will be briefly introduced below. 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 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 A schematic diagram of a system function of a filter according to an embodiment of the present invention;

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

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

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

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

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

[0062] Unless explicitly stated otherwise, throughout the specification and claims, the term “comprise” or variations such as “include” or “comprising”, etc., 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 a specific position or relative relationship. In other words, in some embodiments, the terms "first", "second", etc. can also be interchangeable.

[0064] Combine the following Figures 1 to 6 , describing an embodiment of the present invention.

[0065] In the prior art, 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] Determine 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 a higher slow time sampling rate among the two radars is determined as the first radar. If the slow time sampling rates of the two radars are the same, one of the radars 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 system radar, it refers to the pulse repetition frequency; for a linear frequency modulation continuous wave system 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 implementation of the present invention, the 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 frequency spectrum of the echo signal with 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 the energy 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 through 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 the 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 maximum amplitude point of the time domain waveform whose relative height difference of the peak value is greater than the 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 of the time domain waveform;

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

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

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

[0087] After removing the time intervals not within the interval [m2-σ2, m2+σ2], the mean m3 and the 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 value point refers to the local maximum value of the time domain waveform amplitude of the echo signal.

[0089] Further, in an embodiment of the present invention, selecting a time domain waveform amplitude maximum value point whose peak relative height difference is 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 ], the number of maximum amplitude points of the time domain waveform whose relative height difference of the peak value is greater than the threshold value is calculated at intervals of 0.5 when taking different thresholds, and the number of maximum amplitude points of the time domain waveform whose relative height difference of the peak value is greater than the threshold value is calculated by R threshold values ​​T1, T2, ..., T 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 r ≥3,p r-1 -p r ≤3,r=2,3,…,R, the longest subsequence, the middle 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, according to the local peak value period feature, increasing the slow time sampling rate of the preprocessed second radar echo signal to be the same as the slow time sampling rate of the first radar echo signal;

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

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

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

[0097] Further, 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 nΔt, n = 0, 1, 2, ..., includes:

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

[0099] S109, performing short-time Fourier transform on the preprocessed first radar echo signal to obtain a first time-frequency spectrum; performing 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, respectively, so as to obtain 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, in the time-frequency spectrograms of the first time-frequency spectrum and the second time-frequency spectrum, the micro-Doppler characteristics of the blade time-frequency flicker presented are rectangular flickers perpendicular to the time axis that appear within a certain frequency band. Using this characteristic, the blade time-frequency flicker is mapped into a peak point using Radon transform, and 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 straight 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 straight 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 of the target to be analyzed with enhanced micro-Doppler characteristics;

[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 first Radon transform result and the second Radon transform result after time alignment in the Radon transform domain to obtain a Radon transform result;

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

[0110] An inverse Radon transform is performed 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 degree extracted from the first Radon transform result is defined as the first section data; the section data corresponding to the transformation angle of 0 degree 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 local peak value occurrence period T of the first radar, within the offset time range of (-T / 2, T / 2), the correlation function of the first profile data with 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 time 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] The fused Radon transform result is filtered 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 part of the Radon transform result far away from the angles of 0 degree and 180 degrees can be 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 Radon transform result after filtering for inverse Radon transform; θ is the angle of the straight line along which the integration is performed in the Radon transform relative to the vertical upward direction of the time-frequency spectrum; r is the distance from the straight line along which the integration is performed in the Radon transform to the center of the time-frequency spectrum; ω is the spatial frequency.

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

[0127] The following is a specific 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 carried out using simulated drone radar echo signals. The first radar and the second radar are both 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 Comparison of the simulated UAV echo signal before and after upsampling of the second radar with a slow time sampling rate. Figure 3 Figure a is the echo signal before upsampling, and Figure b is the echo signal after upsampling. It can be seen that Figure a cannot well reflect the periodic peak characteristics caused by the rotation of the UAV rotor due to insufficient slow-time sampling rate, while Figure b better restores the periodic peak 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 of the second radar with a low slow time sampling rate before and after upsampling. 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; Figure a has a certain folding phenomenon in the time-frequency spectrum due to the low slow time sampling rate, 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 flickers, and the time-frequency flickers are 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. The time-frequency spectrum obtained after the upsampling processing using the periodic characteristics of the local peak value of the echo signal provided by the present invention shows that the time-frequency flickers 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 flickers, 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 energy after the change is mainly concentrated near the angles of 0 and 180 degrees, especially 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 diagram, that is, the vertical lines in the time-frequency spectrum diagram.

[0132] Figure 6 The comparison between the time-frequency spectrum directly obtained by the first radar and the second radar and the fused time-frequency spectrum; Figure 6Figure a is the time-frequency spectrum obtained by using short-time Fourier transform of the drone echo signal of the second radar with a low slow-time sampling rate, Figure b is the time-frequency spectrum obtained by using short-time Fourier transform of the drone echo signal of the first radar with a high slow-time sampling rate, and Figure c is the final time-frequency spectrum obtained by fusion enhancement; it can be seen that the time-frequency flicker in Figure c, that is, the periodic vertical line, the drone micro-Doppler feature, is clearer than the other two figures, and the micro-Doppler feature is enhanced. At the same time, the time-frequency spectrum of the fuselage part that does not belong to the micro-Doppler feature, that is, the horizontal line in the time-frequency spectrum, is also effectively removed.

[0133] Quantitative evaluation of time-frequency flicker contrast 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 flickering part; P noise is the average power of the noise.

[0136] The average power of the time-frequency flicker part is calculated according to the following method: for each time-frequency flicker, the mean square value of the main frequency part of the time-frequency flicker at the time of time-frequency flicker in the time-frequency spectrum is calculated, and then the average value of all the mean square values ​​of the time-frequency flicker is taken as the average power of the time-frequency flicker part. 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 a higher frequency that does not contain micro-Doppler characteristics is selected as the noise frequency range, and the average value of the 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-frequency 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] In order to reduce the impact of interference, the noise within 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 gives the comparison of the time-frequency flicker contrast of the time-frequency spectrograms before and after the fusion of the two radars; the time-frequency spectrogram 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, enable the radar with a low slow-time sampling rate to obtain a time-frequency spectrum with enhanced micro-Doppler characteristics of the UAV target by only transmitting the local peak value occurrence period 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 characteristics of the UAV target; and when the amount of data transmission between the two radars is sufficient, a time-frequency spectrum after fusion of the two radar data can be obtained, and the micro-Doppler characteristics of the UAV target in the fused time-frequency spectrum are enhanced compared with those directly obtained from the two radars.

Claims

1. A method for enhancing the micro-Doppler characteristics of a rotary-wing UAV using a dual-station radar, characterized in that: Includes steps: Respectively obtain the 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 comprises: Determine 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 through 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 be the same as the slow time sampling rate of the first radar echo signal; Performing short-time Fourier transform on the preprocessed first radar echo signal to obtain a first time-frequency spectrum; performing 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 transformation on the first time-frequency spectrum to obtain a first Radon transformation result; performing Radon transformation on the second time-frequency spectrum to obtain a second Radon transformation 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 of the target to be analyzed with enhanced micro-Doppler characteristics; Processing the first Radon transform result and the second Radon transform result in a Radon transform domain includes: Performing time alignment on the first Radon transform result and the second Radon transform result in the Radon transform domain; fusing the first Radon transform result and the second Radon transform result after time alignment in the Radon transform domain to obtain a Radon transform result; Performing filtering processing on the fused Radon transform result in the Radon transform domain; An inverse Radon transform is performed 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 ground clutter is translated in the frequency direction, and the peak of the translated spectrum is moved to zero frequency.

3. 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 estimating the 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 time domain waveform amplitude maximum value point whose peak relative height difference is greater than a specified threshold is selected as the candidate peak value; the peak relative height difference is the difference between the time domain waveform amplitude maximum value point and the larger valley point of the valley points on both sides; the specified threshold is a value between 0 and the maximum value of the time domain waveform amplitude; Calculate the time intervals between adjacent candidate peak values; and calculate the mean m1 and standard deviation σ1 of each time interval for the first time; The candidate peak value occurrence time t i , i=1,2,… is the center, if t i The candidate peak value at 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 the 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 is characterized in that: The step of selecting the time domain waveform amplitude maximum value point whose relative height difference of the peak value is greater than a specified threshold as a candidate peak value includes: Define the maximum value of all the time domain waveform amplitude maximum points as P max , in the threshold interval [0,P max ], the number of the maximum value points of the time domain waveform amplitude 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 value point of the time domain waveform amplitude; In the p1,p2,…,p R In the sequence, select the 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 value point of the time domain waveform amplitude 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: According to the local peak value period feature, the slow time sampling rate of the preprocessed second radar echo signal is increased to be the same as the slow time sampling rate of the first radar echo signal, 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], the reconstructed value of the second radar echo signal after upsampling at time nΔt, n = 0, 1, 2, ..., comprises: For the kth moment kΔt after upsampling, calculate the moment value kΔt+mT, m=0, 1, 2, ..., M-1 within the duration of the second radar echo signal; in the second radar echo signal, use the sampling value of the sampling moment with the smallest time difference with kΔtmT as the sampling value of the kth moment kΔt after upsampling of the second radar.

7. 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 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 degree extracted from the first Radon transform result is defined as the first section data; the section data corresponding to the transformation angle of 0 degree extracted from the second Radon transform result is defined as the second section data; the first section data and the second section data take time as the independent variable; the intensity value of the first Radon transform result and the second Radon transform result is the dependent variable; 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 of the first profile data with the second profile data when 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 time 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: The step of fusing the time-aligned first Radon transform result and the second Radon transform result in the Radon transform domain includes: 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 dual-station radar according to claim 1, characterized in that: The fused Radon transform result is filtered 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.

Images