High-speed maneuvering target accumulation detection method under distance-velocity combined deception jamming

Abstract

This invention discloses a method for accumulating and detecting high-speed maneuvering targets under range-velocity joint deception jamming, applied to the field of radar anti-jamming. It addresses the problem that existing technologies struggle to accurately identify range-velocity joint deception jamming and effectively detect high-speed maneuvering targets in multi-static radar systems under low signal-to-noise ratio conditions. First, this invention constructs an echo model of a high-speed maneuvering target under range-velocity joint deception jamming. Then, it proposes a method based on topological Euclidean distance to achieve multi-channel coherent accumulation and acquire target position estimation information for each channel. Finally, it uses hyperbolic-elliptic joint positioning to process the position estimation information, rapidly obtaining the physical target's position estimate and accurately identifying range-velocity joint decoy targets.

Description

Technical Field

[0001] This invention belongs to the field of radar anti-jamming, and specifically relates to a deception jamming identification and target accumulation detection technology. Background Technology

[0002] High-speed maneuvering target detection and identification has always been a research hotspot in the field of radar signal processing, with broad application prospects in both civilian and military fields. Signal accumulation and processing is one of the key aspects of radar moving target detection and identification. However, with the continuous advancement of science and technology and technological innovation, the emergence of a large number of high-speed maneuvering targets has brought severe challenges to their accurate detection. At the same time, the continuous improvement of digital radio frequency memory technology has provided solid technical support for the implementation of deceptive jamming.

[0003] To counter range-velocity combined deception jamming, monostatic radar systems primarily construct a false target identification mechanism by optimizing transmitted waveform design, fusing multi-dimensional parameter information, and addressing differences caused by multiple angles and dimensions such as quantization errors. However, due to its inherent characteristics, monostatic radar suffers from a single observation perspective, resulting in incomplete acquisition of environmental electromagnetic information. Consequently, it struggles to form an effective defense against high-fidelity deception targets.

[0004] Compared to monostatic radar systems, multistatic radar systems can improve interference suppression or identification capabilities through complementary multi-view information. Simultaneously, multistatic radar can acquire both spatial and temporal two-dimensional echoes of targets. By jointly accumulating these echo signals, the radar pulse accumulation gain can be significantly improved. Huang D et al. addressed the problem of range-based false target deception interference in multistatic radar systems. Based on preprocessing of the acquired target angle measurements, they improved the accuracy of target angle measurements in the same direction and proposed an anti-interference technique based on a common-source localization experiment, achieving effective identification of deception interference. Zhao S et al. used a noncoherent accumulation method for target detection and designed a false target discriminator based on the Newman-Pearson criterion, achieving the identification of false targets under noncoherent echo signal accumulation. However, they did not consider the target's phase information, leading to a decrease in accumulation detection performance. LiX et al. proposed a multi-channel SAR hybrid interference suppression algorithm based on grouped iterative separation. This algorithm separates multi-channel signals through preprocessing of the received signal, elimination of interference skipping parts, and iterative solution of optimization problems, and selects the best target signal based on the time-domain peak-to-average power ratio. Gao J et al. proposed a pulse-coded multiple-input multiple-output radar false target interference suppression method based on data correlation beamforming. By decoding and compensating the delayed pulse of the echo matched-filtered signal, the physical target is located on the diagonal of the transmit and receive space frequency domain, thereby realizing the distinction between real and false targets.

[0005] In summary, existing research has achieved the identification and suppression of deception interference through transmit waveform design, utilization of energy or spatial position differences, and non-coherent fusion accumulation, respectively. However, all of these methods have high requirements for signal-to-noise ratio and make it difficult to achieve accurate identification of range-velocity joint deception interference and effective detection of high-speed maneuvering targets in multi-static radar systems under low signal-to-noise ratio conditions. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention proposes a method for detecting the accumulation of high-speed maneuvering targets under range-velocity joint deception interference. This method enables rapid estimation of the physical target position information accumulated through multiple channels and effective identification of range-velocity joint deception interference under different jamming-to-signal ratios (JSR).

[0007] The technical solution adopted in this invention is: a method for detecting the accumulation of high-speed maneuvering targets under range-velocity joint deception jamming, employing a single-transmitter, multi-receiver radar, wherein the transmitter in the single-transmitter, multi-receiver radar transmits signals, and each receiver receives the echo signals; the detection method includes the following steps:

[0008] S1. The echo signal received by each receiver is specifically the superposition of the target echo signal and the range-velocity joint deception interference, thus obtaining the coupled echo of each receiver.

[0009] S2. Perform pulse compression processing on the coupled echo to obtain the pulse compression results of the baseband echo signal of each channel;

[0010] S3. Perform Generalized Radon-Fourier Transform (GRFT) accumulation and threshold preprocessing on the pulse compression results of the baseband echo signals of each channel to obtain the target peak estimation information of the single-channel preprocessing.

[0011] S4. Convert the target peak estimation information into the RVA three-dimensional space to obtain the RVA three-dimensional dataset. Combine the system topology to solve the spatial Euclidean distance between any two targets in the channel.

[0012] S5. Filter the values ​​with equal spatial Euclidean distances and their indices in all channels, extract the unequal indices, keep only one index for indices that appear multiple times, substitute them into the RVA 3D dataset, and obtain the distance, velocity and acceleration values ​​of the target corresponding to each receiver.

[0013] S6. Select one channel as the baseline channel, and exhaustively subtract the position estimates of the remaining channels from the baseline channel estimates to obtain the combination of differences in distance, velocity and acceleration between channels. Select the combination of differences that occurs most frequently as the optimal difference between channels.

[0014] S7. Based on the optimal inter-channel differences, construct the envelope alignment and phase compensation function of the inter-channel echoes to achieve multi-channel coherent accumulation, and use constant false alarm rate (CFAR) to obtain the position estimation result of the system target;

[0015] S8. Based on the position estimation results of the system target in step S7, perform hyperbola-ellipse joint positioning to achieve rapid estimation of the spatial position of the physical target and accurate identification of distance-velocity joint false targets.

[0016] S9. Based on the estimated physical target spatial position and the location and identification results of the distance-velocity joint deception interference in step S8, perform constant false alarm detection processing to obtain the target detection result.

[0017] The beneficial effects of this invention are as follows: This invention extracts the target's trajectory using the GRFT algorithm, while simultaneously correcting for range and Doppler motion caused by the target's velocity and acceleration, obtaining single-channel coherent accumulation results. Next, a method based on topological Euclidean distance is proposed to achieve multi-channel coherent accumulation and obtain estimates of the physical target and range-velocity joint decoys in all channels. Finally, hyperbolic-elliptic joint localization is used to identify the physical target and range-velocity joint decoys. This invention can effectively identify range-velocity joint deception interference and high-speed maneuvering targets under different interference-to-signal ratios, while simultaneously achieving target signal accumulation and enhancement. Attached Figure Description

[0018] Figure 1 This is a flowchart of the present invention.

[0019] Figure 2 This is the accumulated result of a single-channel echo GRFT.

[0020] Among them, (a) is the distance-velocity domain accumulation result of channel 1, (b) is the distance-velocity domain accumulation result of channel 2, (c) is the distance-velocity domain accumulation result of channel 3, (d) is the distance-acceleration domain accumulation result of channel 1, (e) is the distance-acceleration domain accumulation result of channel 2, and (f) is the distance-acceleration domain accumulation result of channel 3.

[0021] Figure 3 This is the result of preprocessing single-channel echo;

[0022] Among them, (a) is the distance-velocity domain preprocessing result of channel 1, (b) is the distance-velocity domain preprocessing result of channel 2, and (c) is the distance-velocity domain preprocessing result of channel 3.

[0023] Figure 4 The dataset consists of a 3D dataset and spatial Euclidean distance results;

[0024] Among them, (a) is the result of the three-dimensional dataset of channel 1, (b) is the result of the three-dimensional dataset of channel 2, (c) is the result of the three-dimensional dataset of channel 3, (d) is the result of the spatial Euclidean distance of channel 1, (e) is the result of the spatial Euclidean distance of channel 2, and (f) is the result of the spatial Euclidean distance of channel 3.

[0025] Figure 5 For multi-channel coherent accumulation and CFAR detection results;

[0026] Among them, (a) is the multi-channel accumulation result in the range-velocity domain, (b) is the multi-channel accumulation result in the range-acceleration domain, (c) is the CFAR detection result in the range-velocity domain, and (d) is the CFAR detection result in the range-acceleration domain.

[0027] Figure 6 The positioning results for the hyperbola and ellipse respectively;

[0028] Among them, (a) is the target hyperbolic positioning result, (b) is the target elliptical positioning result, and (c) is the false target elliptical positioning result under range-velocity joint deception interference;

[0029] Figure 7 The results of hyperbola-ellipse joint localization and recognition;

[0030] Among them, (a) is the result of hyperbolic and elliptical positioning, and (b) is the result of physical target and distance-velocity joint false target identification.

[0031] Figure 8 This is for detecting performance curves. Detailed Implementation

[0032] This invention is verified using Matlab simulation experiments. The correctness and effectiveness of this invention are verified on the scientific computing software Matlab R2022a. The technical solution of this invention is further described below with reference to the accompanying drawings.

[0033] like Figure 1 As shown, the high-speed maneuvering target accumulation detection method proposed in this invention under range-velocity joint deception jamming includes the following steps:

[0034] S1. The one-transmitter-multiple-receiver radar system uses a linear frequency modulation (LFM) signal as the transmitted signal. The down-conversion of the target echo signal received by each receiver can be expressed as:

[0035]

[0036] Among them, S rk (t,t m) represents the target echo from each receiving node of the radar, t is the fast time, c is the electromagnetic wave propagation speed, and A r R represents the amplitude of the echo signal. k (t m The value ) represents the equivalent range history of the target relative to radar system channel k, and its expression is:

[0037]

[0038] Among them, R k V k and a k These can be respectively considered as the target's equivalent initial range, equivalent initial velocity, and initial equivalent acceleration relative to radar system channel k, R. TP R PRk R represents the initial transmit and receive distances, respectively. TP and R PRk Let a represent the initial transmit and receive vectors, respectively. TP and a PRk Let these represent the initial transmit and receive accelerations, respectively, and their expressions are as follows:

[0039]

[0040] Among them, t m denoted by , v represents the target's velocity, and a represents the target's acceleration.

[0041] S t (t) represents the transmitted signal from the radar transmitting node, S t The specific expression for (t) is:

[0042] S t (t)=rect(t / T P )exp[j2πf c t+jπμt 2 ]

[0043] Where rect(·) represents the rectangular pulse modulation function, T p The pulse width is represented by μ = B / T. p The frequency modulation slope is represented by t, where t is the fast time and f is the frequency modulation slope. c This is the signal carrier frequency.

[0044] The down-conversion of the range-velocity combined deception jamming signal received by each receiver can be expressed as:

[0045]

[0046] Among them, J rk (t,t m () represents the interference echoes from each receiving node of the radar. Let N be the amplitude of the range-velocity joint deception jamming, and N be the number of range-velocity joint deception jamming attacks. The equivalent range history of the i-th range-velocity joint dummy target relative to radar system channel k is expressed as:

[0047]

[0048] in, and Let these represent the modulation range and velocity of the i-th dummy target, respectively. and Let represent the time delay offset and Doppler frequency shift of the i-th false target, respectively, where λ is the wavelength;

[0049] The echo signals received by each channel are a superposition of the target signal and range-velocity joint deception interference. Therefore, the baseband echo signal can be expressed as:

[0050] Z k (t,t m ) = S rk (t,t m )+J rk (t,t m )

[0051] Among them, Z k (t,t m () represents the coupled echo waveforms of each receiving node of the radar;

[0052] The radar parameters used in this invention are set as follows: initial carrier frequency f c =0.15GHz, signal bandwidth B = 5MHz, pulse repetition frequency PRF = 500Hz, sampling rate f s =10MHz, pulse width T p =20us, 1 transmitting node, 3 receiving nodes, 300 pulses, single-channel pulse compression signal-to-noise ratio of -15dB, and signal-to-interference ratio of 6dB.

[0053] The nodes mentioned in this step are specifically explained as follows: a multi-static radar includes multiple nodes, and each node is composed of a linear phased array radar.

[0054] S2. By performing pulse compression processing on the coupled echo, the pulse compression results of the baseband echo signals of each channel can be obtained as follows:

[0055]

[0056] in, For the pulse compression waveform of the coupled echo at each receiving node, A e The amplitude of the target echo pulse pressure. Let B be the pulse compression amplitude of the range-velocity joint deception interference, and let B be the signal bandwidth.

[0057] S3. Perform GRFT accumulation and threshold preprocessing on the processed echo signal to obtain the target peak estimation information of a single channel. Threshold preprocessing of the GRFT results of each channel can extract the position information (i.e., distance, velocity, and acceleration) of the target (including physical targets, false targets, etc.). In this embodiment, threshold preprocessing refers to comparing the peak point with a simple adaptive threshold after single-channel accumulation. Those skilled in the art can refer to the CFAR detection principle in practical applications to set an adaptive threshold to complete the threshold preprocessing; this part is a known existing technology and will not be described in detail here.

[0058] Assume that the number of targets exceeding the threshold after each channel threshold preprocessing step is O. k Accordingly, the estimated location information of each channel target can be defined as follows: Among them, O k ≥N t N t =N+1,m k =1,2,…,O k The expression for the single-channel GRFT accumulation output is:

[0059]

[0060] Among them, GRFT k This represents the GRFT processing result for channel k, where M represents the number of pulse accumulations, and R... k Denotes the initial bibase distance history, f(r) k (l k ),v k (n k ),a k (g k ))=r k (l k )-R k ′+(v k (n k )-V k ′)mT r +(a k (g k )-a′ k (mT) r ) 2 A e ′=A e exp(-j2πR k / λ), T r The search parameters r for pulse repetition time, distance, velocity, and acceleration. k (l k ), vk (n k ) and a k (g k ) can be represented as

[0061]

[0062] Among them, l k n k and g k These represent the parameter indices for GRFT distance, velocity, and acceleration, respectively, Δr = c / (2f s ), △v and △a represent the search intervals for distance, velocity and acceleration, respectively. and These represent the number of search units for distance, velocity, and acceleration, respectively. and These represent the search ranges for distance, velocity, and acceleration, respectively, and round(·) represents the rounding up operation.

[0063] The radar parameters used in this invention are set as follows: initial carrier frequency f c =0.15GHz, signal bandwidth B = 5MHz, pulse repetition frequency PRF = 500Hz, sampling rate f s =10MHz, pulse width T p =20µs, pulse count 300. The radar is configured with 1 transmitting node and 3 receiving nodes, with the following parameters: transmitter position (0,0)m, receiver positions 1 to 3 (18280.3,0)m, (24927.3,0)m, and (34145.5,0)m respectively. The initial position of the physical target is (45000,20000)m, and its velocity is (-249.6,-449.7)m·s. -1 The acceleration is (-101.3, -27.4) m·s⁻¹. -2 The range-velocity joint spoofing jamming consists of three elements with modulation parameters of (-7500m, 50m / s), (9000m, -65m / s), and (15000m, 90m / s).

[0064] Figure 2 The accumulated results of single-channel echo GRFT are shown. Figure 2 (a)- Figure 2 (c) The range-velocity domain accumulation results of the three channels are shown respectively. The target did not achieve good accumulation effect, and the range-velocity joint deception interference accumulated obvious peaks. Figure 2 (d)- Figure 2(f) shows the distance-acceleration domain slice results of the physical target velocity in the three channels, which can confirm that the physical target's energy has not accumulated well and its peak value cannot be observed. Figure 3 The results of single-channel echo preprocessing are shown. Figure 3 (a) shows the preprocessing results of channel 1. The target did not accumulate any peak values, and the peak values ​​of the range-velocity joint deception interference were 1190.15, 1257.3, and 1084.89, respectively. Figure 3 (b) shows the preprocessing results of channel 2. The target did not accumulate any peak values, and the peak values ​​of the range-velocity joint deception interference were 1018.57, 1183.34, and 1270.6, respectively. Figure 3 (c) shows the preprocessing results for channel 3. The target did not accumulate any peak values, and the peak amplitudes of the range-velocity joint deception interference were 941.854, 1151.72, and 954.714, respectively. The echo signal-to-noise ratio of a single channel after pulse compression was -15dB. The echo signal was affected by noise, so there were slight differences in the peak amplitudes after single-channel GRFT accumulation.

[0065] S4. Convert the preprocessed estimation information into an RVA 3D dataset, and, combined with the system's topology, solve for the spatial Euclidean distance between any two targets in the channel. The specific implementation method is as follows:

[0066] Based on the preprocessing operations in S3, the position estimation results of the targets in each channel were obtained. By arranging the estimated positions in descending order of peak information and transforming them into RVA 3D space, the spatial Euclidean distance and its index between any two targets in each channel can be calculated, which can be expressed as:

[0067]

[0068] In this context, RVA three-dimensional space represents the three dimensions of distance, velocity, and acceleration, Euclid. k Provides the spatial Euclidean distance data between any two targets in channel k and their indices.

[0069] Figure 4 The results show the 3D dataset and spatial Euclidean distance. Figure 4 (a)- Figure 4 (c) The results of the 3D dataset obtained by data transformation in the three channels are shown respectively. In addition to the range-velocity joint false target, there are many noise points in each channel. Figure 4 (d)- Figure 4 (f) shows the spatial Euclidean distance between any two targets in the three channels.

[0070] S5. Filter all channels for values ​​with equal spatial Euclidean distances and their indices, i.e., the Euclidean distances and indices between system targets. Extract the unequal indices, keeping only one instance of an index that appears multiple times. Substitute these into the 3D dataset to obtain the distance, velocity, and acceleration values ​​of the system targets in each channel. The specific implementation method is as follows:

[0071] The estimated distance, velocity, and acceleration of targets in each channel system can be defined as:

[0072]

[0073] Wherein, T_value k Let θ represent the distance, velocity, and acceleration values ​​between the physical target and the range-velocity joint decoy in channel k. k =1,2,…,O k ′, O k ′ is made by O k The selected sequences. The selection rule is to process indices with equal spatial Euclidean distances across all channels, which are the indices of the targets in each channel system. First, unequal indices are selected, retaining only one occurrence of an index. Then, based on the index number, the corresponding target position estimation result is extracted. The index value acquisition process can be represented as:

[0074]

[0075] Among them, S_Euclid k This represents the set of data and indices indicating equal Euclidean distances. Since the physical target and the range-velocity joint decoys satisfy the same topological structure in spatial distribution, while noise points are randomly distributed, theoretically, the set of spatial Euclidean distances for the three channels contains... The values ​​are equal.

[0076] filter Figure 4 (d)- Figure 4 (f) Spatial Euclidean distance values ​​present in all three tables are marked with dark rectangles. The set of dark rectangle indices is the set of range-velocity joint pseudo-target indices, combined with... Figure 4 (a)- Figure 4 The dataset in (c) provides the position estimation results for the range-velocity joint false target in all channels. In this simulation experiment, the range-velocity joint false target was among the top three estimated targets in all three channels. Taking channel 1 as the baseline, all possible combinations of inter-channel differences (other channels and the reference channel) were exhaustively enumerated, and the combination value that appeared most frequently was selected as the optimal inter-channel difference, i.e., the difference between channel 1 and channel 2 is (5040m, 25m / s, -3m / s). 2 The difference between channel 1 and channel 3 is (10620m, 45m / s, -12m / s).2 ).

[0077] S6. Select any one channel as the baseline channel. Exhaustively subtract the position estimates of the remaining channels from the baseline channel estimate to obtain all possible combinations of differences in distance, velocity, and acceleration between channels. Select the most frequent combination of channel differences as the optimal channel difference. The specific implementation method is as follows:

[0078] The radar system with three receivers (K=3) will be discussed later. Taking channel 1 as the reference channel, the differences between the optimal channels of channel 2 and channel 3 compared to channel 1 can be denoted as follows: They represent △r respectively 12 , △v 12 , △a 12 The estimated value, They represent △r respectively 13 , △v 13 , △a 13 The estimated value. Where, Δr 12 , △v 12 , △a 12 Δr represents the theoretical difference in range, velocity, and acceleration between channel 2 and channel 1 in the radar system. 13 , △v 13 , △a 13 This represents the theoretical differences in range, velocity, and acceleration between channel 3 and channel 1 in the radar system. This is because the differences in range, velocity, and acceleration between targets in the same order system are constant. Therefore, in the differences between channel 2 and channel 1, and between channel 3 and channel 1, N... t In the case of channels 1 and 2, the values ​​are equal, while in other cases they are randomly scattered. Therefore, the inter-channel difference with the highest frequency is selected as the optimal inter-channel difference, where the difference between channel 1 and channel 2 can be expressed as:

[0079]

[0080] The difference between channel 1 and channel 3 can be expressed as:

[0081]

[0082] This is the result of exhaustively subtracting the position estimates of the system target from the baseline channel estimates using the position estimates of the remaining channels obtained from all channels, thus obtaining all possible values ​​of the differences in distance, velocity, and acceleration between channels.

[0083] S7. Based on the optimal inter-channel differences, construct envelope alignment and phase compensation functions for inter-channel echoes to achieve multi-channel coherent accumulation, and use CFAR detection to obtain the position estimation results of the system target. The specific implementation method is as follows:

[0084] The position estimation results of overthreshold targets (physical targets and range-velocity joint false targets) on the multi-channel coherent accumulation plane based on channel 1 can be represented in matrix form as follows:

[0085]

[0086] in, This represents the estimation results of the range, velocity, and acceleration components of the physical target and the range-velocity joint dummy target in channel 1.

[0087] Combining optimal inter-channel differences and The position estimation result of the target in channel 2 is as follows:

[0088]

[0089] in, Diff_R represents the estimation results of the range, velocity, and acceleration components of the physical target and the range-velocity joint dummy target in channel 2. 12 (1) Diff_R 12 (2) Diff_R 12 (3) respectively represent The first, second, and third components.

[0090] Similarly, the target position estimation result for channel 3 can be obtained:

[0091]

[0092] in, Diff_R represents the estimation results of the range, velocity, and acceleration components of the physical target and the range-velocity joint dummy target in channel 3. 13 (1) Diff_R 13 (2) Diff_R 13 (3) respectively represent The first, second, and third components. Additionally, location estimation information exceeding the detection threshold. It is obtained by CFAR detection processing using a multi-channel accumulation plane. Where s = 1, 2, ..., 0 m O m ≥N t The coherent accumulation result of all channels can be expressed as:

[0093]

[0094] The phase compensation function between other channels and channel 1 can be expressed as:

[0095]

[0096] The envelope alignment function between channel 2 and channel 1 can be constructed as follows:

[0097]

[0098] Similarly, the envelope alignment function between channel 3 and channel 1 can be constructed as follows:

[0099]

[0100] Multichannel coherent accumulation and CFAR detection results are as follows Figure 5 As shown. Among them, Figure 5 (a) shows the multi-channel accumulation results in the range-velocity domain, with both the physical target and the range-velocity joint deception interference forming clearly visible peaks; Figure 5 (b) The results of multi-channel accumulation in the range-acceleration domain are shown. Compared with the single-channel accumulation results, the physical target has achieved better accumulation results. Figure 5 (c) The range-velocity domain CFAR detection results are shown. The peak amplitude of the physical target is 1611.91, and the peak amplitudes of the range-velocity joint deception interference are 3145.03, 3591.53, and 3309.06, respectively. Figure 5 (d) shows the CFAR detection results in the range-acceleration domain, with a peak amplitude of 1611.91 for the physical target.

[0101] S8. Based on the target position estimation results from step S7, perform hyperbolic-elliptic joint localization to achieve rapid estimation of the physical target's spatial position and accurate identification of range-velocity joint false targets. The specific implementation method is as follows:

[0102] The core idea of ​​the hyperbolic positioning method is to construct a hyperbolic equation using the equivalent distance difference of the target signal at different receiving stations, and then solve for the intersection of multiple hyperbolas to achieve physical target positioning. For both the physical target and the range-velocity joint dummy target, since the range modulation of the dummy target adds an extra time delay to the physical target's range modulation, the equivalent distance difference between their different transmit and receive channels is the inter-channel distance difference, which is the real axis length 2a of the hyperbola. Simultaneously, the focal position of the hyperbola represents the spatial coordinates of the receivers at different transmit and receive channels, and the focal length 2c represents the distance between these two receivers. Therefore, the position estimates of the physical target and the range-velocity joint dummy target at all channels will construct three identical hyperbolas, and as shown... Figure 6As shown in (a), the intersection of the hyperbola in the first quadrant represents the position coordinates of the physical target. This method can quickly estimate the spatial position of the physical target, but because it constructs the same hyperbola, it cannot identify range-velocity joint false targets.

[0103] Taking any target s as an example, we can construct the hyperbolic equation as follows:

[0104]

[0105] Among them, (x R1 ,y R1 ), (x R2 ,y R2 ) and (x R3 ,y R3 ) represent the positions of receivers 1, 2 and 3 respectively.

[0106] After simplification, the standard hyperbola equation can be obtained.

[0107]

[0108] Among them, the center point (h) of the hyperbola x1 ,h y1 ), (h x2 ,h y2 ), (h x3 ,h y3 The points () represent the midpoints of the two base stations. Here, we take the hyperbola constructed by a one-transmit-one-receive channel and a one-transmit-two-receive channel as an example.

[0109]

[0110] semi-major axis of the hyperbola It is half the difference in equivalent distance between the two channels. The semi-minor axis of the hyperbola can be derived from... The calculations show that the foci of the hyperbola are...

[0111] When radar base stations are located at the same sea level, the following equations are solved simultaneously using the standard hyperbolic equations: and The coordinates of the intersection point of the two hyperbolas can be represented as:

[0112] x1=-a1 2 b2 2 (h x1 -h x2 ) / (a1 2 b2 2 -a2 2 b1 2 )+h x1

[0113]

[0114] Similarly, solving the remaining equations yields (x2, y2) and (x3, y3). Substituting these into the system parameters, we get x1 = x2 = x3, y1 = y2 = y3, and the coordinates of the intersection point are the coordinates of the physical target. Furthermore, elliptical positioning can accurately identify both the physical target and range-velocity joint false targets based on whether a unique focus is generated in the first quadrant. The ellipse equation for any target s can be expressed as:

[0115]

[0116] Wherein, the semi-major axis of the ellipse The focal length of the ellipse is 2c, which is half the estimated radial distance of target s in channel k. k =x Rk Let be the distance between the transmitting station and the receiving station in channel k.

[0117] Using mathematical methods to solve the equation of an ellipse Solving the system of equations simultaneously, the coordinates of the intersection points of the corresponding ellipses can be expressed as:

[0118] x 12 =-a1 2 b2 2 (x R1 -x R2 ) / (2a1 2 b2 2 -2a2 2 b1 2 )+x R1 / 2

[0119]

[0120] Similarly, solving the remaining combinations of the above equation yields x. 13 y 13 x 23 and y 23 Substituting the system parameters from above, if target s is the real target, then we can obtain x. 12 =x 13 =x 23 y 12 =y 13 =y 23 If the target s is a range-velocity deception, then x can be obtained. 12 ≠x 13 ≠x 23 y 12 ≠y 13 ≠y 23 That is, for example Figure 6 As shown in (b), the real target must lie on the circumference of each ellipse, and as... Figure 6 (c) Range-velocity joint deception jamming on each channel will not satisfy the above results because it does not conform to the topology of a one-transmitter-multiple-receiver radar system. In summary, hyperbolic-elliptic joint localization processing can achieve multiple accurate identifications of physical targets and range-velocity joint decoys.

[0121] The results of hyperbolic-elliptic joint localization and recognition are as follows: Figure 7 As shown. Among them, Figure 7 (a) shows the results of hyperbolic and elliptical localization. It can be seen that the physical target positions obtained by hyperbolic and elliptical localization coincide in the first quadrant, while the elliptical localization results for the range-velocity joint false target do not converge at a single point. Based on this, the identification results of the physical target and the range-velocity joint false target are determined by... Figure 7 As shown in (b).

[0122] S9. Based on the location and identification results of the physical target and the distance-velocity joint deception interference in step S8, perform constant false alarm detection processing to obtain the target detection result.

[0123] Figure 8 The detection performance curves of the proposed method against target and range-velocity joint deception interference are shown under different interference-to-signal ratios. The false alarm probability is P. f =10 -3 The input signal-to-noise ratio (SNR) after pulse compression ranges from -30dB to -5dB. Figure 8 It can be seen that, under the same signal-to-noise ratio, the target detection probability gradually increases with the increase of JSR. This is because the increase of JSR enhances the energy distribution of the range-velocity joint decoy, resulting in higher accuracy in parameter estimation and effective improvement in the accuracy of physical target echo signal accumulation processing. However, when JSR exceeds the critical threshold of 12dB, the system parameter estimation performance enters the saturation range. At this point, the marginal gain effect of the detection probability is significantly weakened, meaning that the target detection probability no longer shows a significant gain. Therefore, the method proposed in this invention can still effectively identify range-velocity joint deception interference and accumulate and detect high-speed maneuvering target signals even under varying interference amplitudes.

[0124] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the scope of the claims of the invention.

Claims

1. A method for accumulation detection of high-speed maneuvering targets under combined distance-velocity deception jamming, characterized in that, A single-transmitter, multiple-receiver radar is used, wherein the transmitter in the radar emits a signal, and each receiver receives the echo signal; the detection method includes the following steps: S1. The echo signal received by each receiver is specifically the superposition of the target echo signal and the range-velocity joint deception interference, thus obtaining the coupled echo of each receiver. S2. Perform pulse compression processing on the coupled echo to obtain the pulse compression results of the baseband echo signal of each channel; S3. Perform GRFT accumulation and threshold preprocessing on the pulse compression results of the baseband echo signals of each channel to obtain the target peak estimation information of the single-channel preprocessing. S4. Convert the target peak estimation information to... In three-dimensional space, we obtain Using a 3D dataset and the system's topology, the spatial Euclidean distance between any two targets in the channel is calculated. S5. Filter all channels for values ​​with equal spatial Euclidean distance and their indices. Extract the unequal indices, keeping only one instance of an index that appears multiple times, and substitute it into the... The three-dimensional dataset yields the distance, velocity, and acceleration values ​​of the target corresponding to each receiver. S6. Select one channel as the baseline channel, and exhaustively subtract the position estimates of the remaining channels from the baseline channel estimates to obtain the combination of differences in distance, velocity and acceleration between channels. Select the combination of differences that occurs most frequently as the optimal difference between channels. S7. Based on the optimal inter-channel difference, construct the envelope alignment and phase compensation function of the inter-channel echo to realize multi-channel coherent accumulation, and use constant false alarm rate detection to obtain the position estimation result of the system target; S8. Based on the position estimation results of the system target in step S7, perform hyperbola-ellipse joint positioning to achieve rapid estimation of the spatial position of the physical target and accurate identification of distance-velocity joint false targets. S9. Based on the estimated physical target spatial position and the location and identification results of the distance-velocity joint deception interference in step S8, perform constant false alarm detection processing to obtain the target detection result.

2. The method of claim 1, wherein, The coupled echo in step S1 is represented as: ； in, Indicates the first Coupled echo of a receiver, Indicates the first The target echo signal of the receiver Indicates the first Range-velocity combined deception and jamming of individual receivers. To save time, It indicates a slow time.

3. The method of claim 2, wherein, The expression is: ； in, For the amplitude of the range-velocity joint deception interference, The number of range-velocity joint deception jammers. Indicates the first The distance-velocity joint decoy relative to the first The equivalent distance history of each receiver This indicates the transmitted signal of the radar transmitting node. This is the signal carrier frequency.

4. The method of claim 3, wherein, The pulse pressure result in step S2 is expressed as follows: ； in, The pulse compression waveform of the coupled echo at each receiving node. The amplitude of the target echo pulse pressure. The pulse compression amplitude for range-velocity joint deception interference. For signal bandwidth, Indicates the target relative to the radar system channel The equivalent distance to history, It is the wavelength.

5. The method of claim 4, wherein, Let the reference channel number be n. Then, the phase compensation function between the other channels and channel n in step S7 is expressed as: ； wherein denotes a phase compensation function between channel g and channel n, denotes an estimate of the theoretical distance difference between channel g and channel n.

6. The method of claim 5, wherein, The envelope alignment function between other channels and channel n in step S7 is expressed as follows: ； wherein, denotes an envelope alignment function between channel g and channel n, , , denotes search parameters for distance, velocity and acceleration, denotes an estimate of the velocity difference between channel g and channel n, denotes an estimate of the acceleration difference between channel g and channel n.

7. The method of claim 6, wherein, The process of hyperbola-ellipse joint positioning in step S8 is as follows: Construct the equation of the hyperbola; specifically: the length of the real axis of the hyperbola is denoted as... The focal length of the hyperbola is denoted as . , This represents the difference in equivalent radial distance between the real target and the dummy target across different transmit and receive channels. The Euclidean distance between the spatial locations of different receiving stations; Physical target localization is achieved by solving for the intersection points of multiple hyperbolas; Construct the equation of the ellipse; specifically: denoted as the semi-major axis of the ellipse. The focal length of the ellipse is denoted as . , For the system target in the channel Half of the estimated radial distance. For channel The distance between the transmitting station and the receiving station; If the coordinates of the intersection point of the ellipse are in the first quadrant and produce a unique intersection point, then it is a real target; otherwise, it is a range-velocity combined false target.

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