Weak target energy accumulation strategy and method for multi-base heterogeneous platform

Abstract

The invention discloses a weak target energy accumulation strategy and method for a multi-base heterogeneous platform. The method comprises the following steps: firstly, for three heterogeneous platforms of air-based, land-based and sea-based, screening out a long-time coherent accumulation algorithm suitable for the three heterogeneous receiving platforms on the basis of algorithm operation complexity consideration performance so as to realize target energy accumulation in nodes; besides, in consideration of the problem that multi-base indirect received waves have obvious difference in target distance and Doppler parameters, alignment and fusion of target echo energy among multiple nodes are completed by establishing a non-coherent accumulation mathematical mapping relation of receiving platforms, effective improvement of target energy is realized, and the detection capability of maneuvering weak targets is enhanced. The invention particularly provides a relatively clear long-time accumulation method selection strategy and a signal accumulation method of different transform domain accumulation results aiming at the problem of signal level accumulation of the existing distributed heterogeneous platform. Therefore, the method has high practical value and wide application prospect.

Description

Technical Field

[0001] The present invention relates to the field of radar detection technology, and in particular to a weak target energy accumulation strategy and method for a multi-base heterogeneous platform. Background Art

[0002] With the increasing complexity of electromagnetic space and the increasingly severe battlefield situation, multi-platform collaborative observation can help to significantly improve combat effectiveness. The "three-level" fusion method of signal level, data level, and intelligence level has the ability to systematically enhance multi-platform collaborative detection. Among them, compared with the data level and intelligence level, which mine and obtain target information at the point and track levels, the signal level accumulation directly uses the original echo signal for information fusion, thereby obtaining the characteristic information of the target to the greatest extent. Therefore, the multi-platform joint signal-level target energy accumulation method is of great significance to improving the weak target detection capability.

[0003] The existing distributed receiving coherent method mainly considers the coherent synthesis of pulse signals. Multiple mobile unit radars or antennas are dispersedly arranged. By performing signal-level coherent synthesis on the echoes of multiple radars, a powerful detection radar is equivalently formed. After time delay and phase compensation, the received signals are aligned in time and phase, and the signals of different receiving channels can be coherently superimposed. At this time, the addition of N receiving channel signals can provide N times the signal-to-noise ratio benefit. At present, distributed coherent technology has strict requirements on the spatial geometric configuration between the target and the distributed nodes; the radial acceleration of high-speed maneuvering targets will also cause the Doppler nonlinear expansion effect of the echo signal, and the target energy will be seriously defocused, which seriously restricts the performance of this method. When multiple nodes observe high-maneuvering target scenes, the current typical technology is a multi-channel target energy accumulation method based on a distributed MIMO system. This method considers using full-dimensional search methods such as GRFT and RFT in multiple channels to first complete the intra-channel accumulation, and then construct the inter-channel envelope and phase compensation function to complete the inter-channel accumulation.

[0004] Coherent synthesis technology represented by distributed receiving coherence is also called distributed aperture synthesis. However, this type of platform is mainly composed of multiple receiving platforms of the same type, and the multi-node echo synthesis at the receiving end is easily affected by the parameter estimation results. For weak targets with high-speed maneuvers, the received echo is usually weak. At this time, it is difficult for distributed receiving coherent technology to directly estimate the motion parameters, which greatly limits the use of this technology in weak target environments; at the same time, the above-mentioned MIMO-GRFT multi-channel accumulation technology also has three main problems in actual use: 1) This method is still aimed at the same type of platform. In the scenario of heterogeneous multi-receiving platforms, the distance migration phenomenon and Doppler diffusion degree of the received echo of each platform are different due to the different geometric configurations of the transmitter, target and receiving station during the long-term accumulation process of air-based nodes, land-based nodes and sea-based nodes. At this time, if the GRFT method is used for all platforms, it will bring a huge overhead load, and the full-dimensional search calculation seriously increases the processing load of the airborne platform. Different receiving load platforms need to select more reasonable algorithms, rather than multiple platforms sharing the same accumulation algorithm. Therefore, for actual detection scenarios, it is particularly important to select a long-term accumulation algorithm that is suitable for each platform; 2) Heterogeneous multi-platforms are usually deployed in a larger detection range. Even if the transmitter uses wide beam coverage, the multi-angle span difference will still cause the target scattering cross-sectional area fluctuation characteristics to be unstable. The echo coherence at the receiving end between multiple platforms is still difficult to meet, and the coherent accumulation results of multiple platforms have a large performance loss. Non-coherent technology can efficiently aggregate energy from heterogeneous multi-platforms, thereby greatly improving the detection capability of weak targets, but how to aggregate target energy from multiple platforms urgently needs in-depth research. 3) The fusion configuration of different long-term accumulation algorithm results puts forward new requirements for the processing algorithm. At present, the industry lacks corresponding methods to solve the signal-level fusion accumulation problem of accumulation results in different transform domains, parameter domains, and time-frequency domains. Summary of the invention

[0005] The present invention provides a weak target energy accumulation strategy and method for a multi-base heterogeneous platform, thereby solving the signal energy accumulation problem of a maneuvering target in the beam space dimension or signal level under a satellite-borne illumination source-multi-base heterogeneous platform receiving system in the prior art, and realizing that the parameter differences between nodes can be quickly estimated through a graph node set and a voting accumulation method, and then a compensation function is constructed to achieve envelope alignment and accelerate non-coherent accumulation.

[0006] The present invention provides a weak target energy accumulation strategy and method for a multi-base heterogeneous platform, the method comprising:

[0007] Constructing a dual-base distance history mathematical model of a heterogeneous receiving platform, and obtaining a dual-base distance history expression of the dual-base distance history according to the dual-base distance history mathematical model;

[0008] Acquire target echo signals corresponding to the plurality of heterogeneous receiving platforms, perform matched filtering on the target echo signals to obtain range-compressed echo signals, and perform the following processing on the range-compressed echo signals corresponding to each of the heterogeneous receiving platforms:

[0009] Combining the distance-compressed echo signal with the dual-base distance history expression to obtain a first echo signal; wherein the heterogeneous receiving platform includes: an air-based platform, a land-based platform, and a sea-based platform;

[0010] Using different algorithms for different base platforms in the heterogeneous receiving platform to perform intra-node target energy accumulation calculation on the first echo signal, so as to obtain the first frequency domain echo signal corresponding to each base platform and the intra-node coherent accumulation result;

[0011] A low threshold method is used to roughly estimate the coherent accumulation results within the nodes corresponding to each base platform, and a graph node set of the platform dual base is constructed based on the rough estimation results; and the graph node set is screened using a voting accumulation method to obtain the maximum value of the graph node set; and the optimal estimation node corresponding to the optimal accumulation node is determined based on the maximum value;

[0012] A compensation function corresponding to each base platform in the heterogeneous receiving platform is constructed according to the optimal estimation node, and the first frequency domain echo signal corresponding to each base platform is compensated by using the compensation function, and non-coherent accumulation is performed on each base platform to obtain a non-coherent accumulation result, thereby completing the signal-level weak target energy accumulation of multiple base heterogeneous platforms.

[0013] In a possible implementation, the dual-base distance history mathematical model is expressed as:

[0014] R(t m )=‖R TP (t m )‖+‖R RP (t m )‖-‖R TR (t m )||;

[0015] Among them, R TP (t m ) represents the distance history between the irradiation source satellite and the target; R TR (t m ) represents the distance history between the illumination source satellite and the multi-base heterogeneous receiving platform; R RP (t m ) represents the distance history between the multi-base heterogeneous receiving platform and the target; ||·|| represents the Euclidean norm of the vector.

[0016] In a possible implementation, acquiring target echo signals corresponding to the plurality of heterogeneous receiving platforms, performing matched filtering on the target echo signals, and obtaining range-compressed echo signals includes:

[0017] Determine the transmission signal emitted by the irradiation source satellite to the ground;

[0018] According to the dual-base distance relationship, target echo signals corresponding to the plurality of heterogeneous receiving platforms are obtained;

[0019] The target echo signal and the direct wave are cross-correlated to obtain range-compressed echo signals corresponding to the plurality of heterogeneous receiving platforms.

[0020] In a possible implementation, the range-compressed echo signal is expressed as:

[0021]

[0022] Among them, A i represents the signal amplitude after pulse compression of the i-th receiving platform; B represents the signal bandwidth; R TP (t m ) represents the distance history between the irradiation source satellite and the target; R RP,i (t m ) represents the distance history between the multi-base heterogeneous receiving platform and the target; R TR,i (t m ) represents the distance history between the irradiation source satellite and the multi-base heterogeneous receiving platforms.

[0023] In a possible implementation manner, the first echo signal is expressed as:

[0024]

[0025] Among them, A i represents the signal amplitude after pulse compression of the i-th receiving platform; B represents the signal bandwidth; t n Indicates fast time; t m Indicates slow time; R 0,i represents the equivalent dual-base initial distance between the i-th receiving platform and the target; v i represents the equivalent radial velocity between the i-th receiving platform and the target; a i represents the equivalent radial acceleration between the i-th receiving platform and the target; c represents the speed of light; λ represents the carrier wavelength.

[0026] In a possible implementation manner, the using different algorithms for different base platforms in the heterogeneous receiving platform to perform accumulation calculation of target energy within a node on the first echo signal includes:

[0027] The air-based platform adopts a TRT-based algorithm to achieve target energy accumulation within the node;

[0028] The land-based platform adopts GRFT-based algorithm to achieve target energy accumulation within the node;

[0029] The sea-based platform adopts a KT-based algorithm to achieve target energy accumulation within the node.

[0030] In a possible implementation manner, constructing a compensation function corresponding to each base platform in the heterogeneous receiving platform according to the optimal estimation node, and using the compensation function to compensate the first frequency domain echo signal corresponding to each base platform, includes:

[0031] Determining optimal estimation parameters of each base platform in the heterogeneous receiving platform according to the optimal estimation node;

[0032] Determine a parameter compensation function corresponding to each base platform according to the optimal estimated parameter, and use the parameter compensation function corresponding to each base platform to compensate the first frequency domain echo signal corresponding to each base platform to obtain a first compensation signal corresponding to each base platform;

[0033] The reference node of each base platform is determined, and a compensation function is constructed based on the parameter differences corresponding to the remaining base platforms according to the reference node and the optimal estimation node.

[0034] In a possible implementation, performing non-coherent accumulation on each base platform to obtain a non-coherent accumulation result and completing signal-level weak target energy accumulation on multiple base heterogeneous platforms includes:

[0035] Constructing a compensation function according to the parameter difference to correct the first frequency domain echo signal corresponding to each base platform to obtain a correction signal corresponding to each base platform;

[0036] By utilizing the correction signals corresponding to the base platforms, non-coherent accumulation is performed on each base platform to obtain a non-coherent accumulation result, thereby completing the signal-level weak target energy accumulation of multiple base heterogeneous platforms.

[0037] In a possible implementation, the optimal estimation node is expressed as:

[0038]

[0039] Among them, Y m,n,q represents the voting result; m represents the number of nodes in the first set of the graph node set; n represents the number of nodes in the second set of the graph node set; q represents the number of nodes in the third set of the graph node set; argmax{·} represents the maximum value function.

[0040] In a possible implementation, the non-coherent accumulation result is expressed as:

[0041]

[0042] Among them, f r represents the distance frequency domain variable; t m represents a slow time variable; Indicates the signal after compensation of the air-based platform; represents the distance difference compensation function of the land-based platform; Indicates the signal after compensation of the land-based platform; Indicates the signal after compensation of the sea-based platform; represents the distance difference compensation function of the sea-based platform; t n represents the fast time variable; f m represents the pulse-dimensional frequency domain variable.

[0043] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0044] The present invention firstly establishes a dual-base distance history mathematical model under a three-dimensional space geometric configuration of one send and multiple receive, and constructs a universal received echo signal expression for heterogeneous multi-receiving platforms; the present invention accumulates signals within the node in the first step of the processing stage, and uses the TRT-based method to complete the target energy accumulation within the node for the air-based node; for the land-based platform, the GRFT-based method is used to transform the target state into the parameter domain while completing the target energy accumulation; and for the sea-based platform, the robust KT-based method that takes both complexity and performance into consideration is used to achieve energy focusing on weak targets; the present invention accumulates signals between nodes in the second step of the processing stage, and constructs a target graph node set by roughly extracting the accumulation results of each platform by setting a low threshold. Furthermore, based on the idea of ​​voting accumulation, the target state information between graph nodes is transmitted and accumulated, and after obtaining the preprocessing results, the peak relationship is used to eliminate the remaining false targets and retain the optimal graph nodes. The parameter estimation results are then used to construct a compensation function for the envelope difference compensation of each node relative to the reference node. Finally, the non-coherent accumulation operation is used to realize the weak target energy accumulation between the three heterogeneous nodes of air-based, land-based and sea-based. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A flow chart of weak target energy accumulation strategy and method steps for a multi-base heterogeneous platform provided by an embodiment of the present invention;

[0046] Figure 2 A schematic diagram of the spatial geometric configuration of a multi-base heterogeneous receiving platform provided in an embodiment of the present invention;

[0047] Figure 3A schematic diagram of graph node link transmission provided by an embodiment of the present invention;

[0048] Figure 4a A result diagram of a range compression signal of an echo received by an air-based platform provided in an embodiment of the present invention;

[0049] Figure 4b A result diagram of a land-based platform receiving an echo range compression signal provided in an embodiment of the present invention;

[0050] Figure 4c A result diagram of a range compression signal of an echo received by a sea-based platform provided in an embodiment of the present invention;

[0051] Figure 5a The accumulated results after parameter compensation of the air-based receiving platform provided in the embodiment of the present invention;

[0052] Figure 5b The accumulated results after parameter compensation of the land-based receiving platform provided in the embodiment of the present invention;

[0053] Figure 5c The accumulated results after parameter compensation of the sea-based receiving platform provided in the embodiment of the present invention;

[0054] Figure 5d The signal-level non-coherent accumulation result of the multi-base heterogeneous platform provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The present invention provides a weak target energy accumulation strategy and method for a multi-base heterogeneous platform, such as Figure 1 As shown, the method includes the following steps S101 to S105.

[0057] S101, constructing a dual-base distance history mathematical model of a heterogeneous receiving platform, and obtaining a dual-base distance history expression of the dual-base distance history according to the dual-base distance history mathematical model;

[0058] Specifically, in step S101, the dual-base distance history mathematical model is expressed as:

[0059] R(t m )=||R TP (t m )||+||R RP (t m )||-||RTR (t m )||;

[0060] Among them, R TP (t m ) represents the distance history between the irradiation source satellite and the target; R TR (t m ) represents the distance history between the illumination source satellite and the multi-base heterogeneous receiving platform; R RP (t m ) represents the distance history between the multi-base heterogeneous receiving platform and the target; ||·|| represents the Euclidean norm of the vector.

[0061] Exemplarily, the present invention is mainly aimed at the detection scenario of mobile weak targets in the air under the one-transmit-multiple-receive system in a distributed radar system, with a satellite illumination source as an external radiation source and heterogeneous receiving platforms deployed in air, land and sea as receiving nodes. Firstly, assuming that the illumination source system transmits a linear frequency modulation LFM signal, three multi-base heterogeneous platforms are used to receive the reflected signal of the mobile target, and the speed and distance measurement mathematical model under the general geometric configuration of the one-transmit-multiple-receive system is derived, and the corresponding receiving signal mathematical model is established.

[0062] Specifically, if Figure 2 The figure shows the spatial geometric configuration of the multi-base heterogeneous receiving platform. The parameters that need to be initialized mainly include: the spatial position parameters, velocity parameters, and acceleration parameters of the multi-base heterogeneous receiving platform, the spatial position parameters, velocity parameters, and acceleration parameters of the satellite illumination source, and the spatial position parameters, velocity parameters, and acceleration parameters of the maneuvering target.

[0063] According to the above parameters, the distance history between the irradiation source satellite and the target, the distance history between the multi-base heterogeneous receiving platform and the target, and the distance history between the irradiation source satellite and the multi-base heterogeneous receiving platform can be expressed as:

[0064]

[0065] Among them, R TP0 represents the initial distance vector between the source satellite and the target, v T represents the spatial velocity vector of the irradiation source satellite, a T R represents the spatial acceleration vector of the irradiation source satellite; RP0,i represents the initial distance vector between the multi-base heterogeneous receiving platform and the target, v R,i represents the spatial velocity vector of the i-th multi-base heterogeneous receiving platform, a R,i represents the spatial acceleration vector of the i-th multi-base heterogeneous receiving platform. The above distance history vector is converted into a scalar and m = 0, and the second-order approximate Taylor expansion is obtained:

[0066]

[0067] According to the spatial geometric configuration relationship, the double-base distance history of the target can be expressed as:

[0068] R(t m )=||R TP (t m )||+||R RP (t m )||-||R TR (t m )|| (7)

[0069] Where ||·|| represents the Euclidean norm of the vector. Substituting the above distance history scalar, the double base distance history scalar of the target is further expressed as:

[0070]

[0071] Simplifying the above formula, we can get:

[0072]

[0073] Therefore, the dual-base distance history between the multi-base heterogeneous receiving platform and the target can be simplified as:

[0074]

[0075] Among them, R i represents the dual-base distance history between the i-th receiving platform and the target, R 0,i represents the equivalent dual-base initial distance between the i-th receiving platform and the target, v i represents the equivalent radial velocity between the i-th receiving platform and the target, a i represents the equivalent radial acceleration between the i-th receiving platform and the target.

[0076] S102, acquiring target echo signals corresponding to multiple heterogeneous receiving platforms, performing matched filtering processing on the target echo signals to obtain range-compressed echo signals, and performing the following processing on the range-compressed echo signals corresponding to each of the heterogeneous receiving platforms:

[0077] The first echo signal is obtained by combining the echo signal of range compression and the dual-base range history expression; wherein the heterogeneous receiving platform includes: an air-based platform, a land-based platform and a sea-based platform;

[0078] Specifically, in step S102, target echo signals corresponding to multiple heterogeneous receiving platforms are acquired, and matched filtering is performed on the target echo signals to obtain range-compressed echo signals, including the following steps S1021 to S1023.

[0079] S1021, determining a transmission signal emitted by the illumination source satellite to the ground;

[0080] S1022, obtaining target echo signals corresponding to multiple heterogeneous receiving platforms according to the dual-base distance relationship;

[0081] S1023, cross-correlation processing is performed on the target echo signal and the direct wave to obtain range-compressed echo signals corresponding to multiple heterogeneous receiving platforms.

[0082] Exemplarily, assuming that the illumination source satellite transmits a linear frequency modulation signal to the ground, the transmitted signal can be expressed as:

[0083]

[0084] Where rect(·) represents the rectangular window function, T p Indicates pulse width, μ=B / T P represents the modulation frequency, B represents the signal bandwidth, f c represents the carrier frequency, and t represents the full-dimensional time.

[0085] Ignoring noise and clutter, the two-dimensional echo signal emitted by the source satellite and received by the i-th heterogeneous platform can be expressed as:

[0086]

[0087] in, represents the complex amplitude of the echo signal of the i-th heterogeneous receiving platform, β i represents the target echo signal level value of the i-th receiving platform, φ i ~N(μ,σ 2 ) represents the phase change of the received signal due to different viewing angles. Performing down-conversion operation on equation (12) yields:

[0088]

[0089] At the same time, the direct wave signal corresponding to the i-th receiving platform can be expressed in the two-dimensional time domain as:

[0090]

[0091] Next, the target echo and the direct wave of the i-th receiving platform are cross-correlated to compress the target signal in the range direction. The echo signal after pulse compression of the i-th receiving platform (the echo signal with range compression) can be expressed as:

[0092]

[0093] Among them, A irepresents the signal amplitude after pulse compression of the i-th receiving platform; B represents the signal bandwidth; R TP (t m ) represents the distance history between the irradiation source satellite and the target; R RP,i (t m ) represents the distance history between the multi-base heterogeneous receiving platform and the target; R TR,i (t m ) represents the distance history between the irradiation source satellite and the multi-base heterogeneous receiving platforms.

[0094] Substituting the simplified distance history expression, the above formula can be simplified to the first echo signal:

[0095]

[0096] Among them, A i represents the signal amplitude after pulse compression of the i-th receiving platform; B represents the signal bandwidth; t n Indicates fast time; t m Indicates slow time; R 0,i represents the equivalent dual-base initial distance between the i-th receiving platform and the target; v i represents the equivalent radial velocity between the i-th receiving platform and the target; a i represents the equivalent radial acceleration between the i-th receiving platform and the target; c represents the speed of light; λ represents the carrier wavelength.

[0097] S103, using different algorithms for different base platforms in the heterogeneous receiving platform to perform intra-node target energy accumulation calculation on the first echo signal, to obtain the first frequency domain echo signal corresponding to each base platform and the intra-node coherent accumulation result;

[0098] Specifically, in step S103, different algorithms are used for different base platforms in the heterogeneous receiving platform to perform accumulation calculation of the target energy within the node on the first echo signal, including:

[0099] The air-based platform uses a TRT-based algorithm to achieve target energy accumulation within the node;

[0100] The land-based platform uses the GRFT-based algorithm to achieve target energy accumulation within the node;

[0101] The sea-based platform adopts KT-based algorithm to achieve target energy accumulation within the node.

[0102] Here, since the load space and load-bearing capacity of the airborne platform are limited, the onboard signal processing capability is limited, so the airborne platform is suitable for long-term accumulation algorithms with low computational complexity. The TRT-based algorithm can quickly eliminate the odd terms of high-order maneuvering parameters by flipping the range frequency domain along the slow time dimension and then conjugating and multiplying the original data, greatly reducing the range migration and Doppler spread, and has high computational efficiency. This algorithm is suitable for load-constrained platforms such as airborne.

[0103] The land-based platform uses computer equipment with large-scale powerful processing units to enhance the computing power of the system, and does not strictly require the algorithm's computational complexity and efficiency. The GRFT-based algorithm has been proven to be an algorithm with excellent coherent accumulation performance. The multi-dimensional search operation of the algorithm can be decomposed into multiple parallel processing units for synchronous execution, so it is very suitable for executing this operation on the ground-based platform with large-scale parallel computing processors.

[0104] Sea-based platforms are usually deployed on buoys or ships with undulating waves, which requires high robustness of the algorithm and seeks a balance between computational complexity and accumulation performance. At this time, the KT-based algorithm eliminates the first-order range migration caused by the unambiguous velocity through the first-order KT transform, and then constructs a two-dimensional compensation function of the fuzzy factor and acceleration to match the frequency domain echo signal after KT. Therefore, it can effectively deal with the accumulation problem of weak targets on sea-based platforms.

[0105] Exemplarily, the airborne platform uses a TRT-based algorithm to perform range migration and Doppler spread correction to achieve coherent accumulation of target energy within a node.

[0106] First, the received echo signal of the airborne node is converted to the range frequency domain, and the first echo range frequency domain signal is expressed as:

[0107]

[0108] Among them, σ air represents the target scattering coefficient of the airborne node, f r Represents the frequency variable in the distance frequency domain, R air represents the equivalent dual-base initial distance between the airborne receiving platform and the target, v air The equivalent radial velocity between the airborne receiving platform and the target, α air Represents the equivalent radial acceleration between the airborne receiving platform and the target.

[0109] Usually, the satellite-borne illumination source continuously transmits signals to the ground at a low pulse repetition frequency. Therefore, the target equivalent true radial velocity can be expressed as:

[0110] v air =v b,air +Mv,air V u (18)

[0111] Among them, v b,air represents the unambiguous velocity corresponding to the airborne node target echo, M v,air represents the velocity fuzzy number corresponding to the airborne node target echo, V u Indicates the blind speed corresponding to the air-based node.

[0112] Perform the time domain conjugate flip self-multiplication operation on the first echo range frequency domain signal to obtain the first echo range compensation signal:

[0113]

[0114] Further using the traditional KT wedge transformation method to eliminate the range migration phenomenon caused by radial velocity, we can get:

[0115]

[0116] The compensation function for the residual distance movement is constructed as follows:

[0117]

[0118] Further use of compensation function and s TRT-KT (f r ,t a ) to eliminate the fuzzy factor effect, and perform IFFT operation along the range frequency domain to obtain the first echo time-frequency domain signal:

[0119]

[0120] From formula (22), it can be seen that the time-frequency domain signal envelope of the first echo has been concentrated in the same distance unit. At this time, the unambiguous speed of the target can be estimated by using the peak extraction technology, and the actual speed of the airborne node target echo can be estimated according to the searched speed ambiguity factor as follows:

[0121]

[0122] The compensation function is constructed using the estimated velocity result to eliminate the velocity term of the original range frequency domain echo, and the second echo range frequency domain echo can be obtained:

[0123]

[0124] Furthermore, the range-frequency domain flip multiplication operation is performed on the second echo range-frequency domain echo, and the following is obtained:

[0125]

[0126] Perform IFFT transformation on the above equation to the fast time domain:

[0127]

[0128] The acceleration compensation function is constructed as follows:

[0129]

[0130] By using this compensation function to eliminate the acceleration ambiguity phase term, we can get:

[0131]

[0132] Performing NUFFT operation on the above signal along the slow time dimension yields:

[0133]

[0134] Using the acceleration fuzzy factor and the peak estimation result, the acceleration is estimated as follows:

[0135]

[0136] Using the above velocity and acceleration estimates to compensate for the first echo of the range frequency, we can obtain:

[0137]

[0138] Transforming the above signal into the distance time domain, we can get:

[0139]

[0140] Perform an FFT operation along the slow time dimension and use peak detection techniques to estimate the equivalent initial distance At this time, for the airborne receiving node, the target's equivalent dual-base initial distance, equivalent initial velocity and equivalent acceleration can be effectively estimated.

[0141] The land-based platform uses the GRFT-based algorithm to perform a three-dimensional joint search of distance, velocity, and acceleration, and gives the accumulated results.

[0142] Get the received echo after distance compression of the land-based platform:

[0143]

[0144] Among them, A land Indicates the amplitude of the echo signal received by the land-based node, R land represents the equivalent dual-base initial distance between the land-based receiving platform and the target, v land is the equivalent radial velocity between the land-based receiving platform and the target, α land Represents the equivalent radial acceleration between the land-based receiving platform and the target.

[0145] The essence of the GRFT-based algorithm is to extract and accumulate the energy of echo signals along the motion trajectory searched by multi-dimensional parameters. Each search value combination of distance, speed and acceleration will correspond to a target motion trajectory to be extracted, and coherent superposition will be achieved after phase compensation. If and only if the search value matches the true value, the target echo signal energy will be completely extracted and coherently superimposed to form a maximum value. Using the above idea, the GRFT-based algorithm is executed on the received echo after distance compression of the land-based platform to obtain the first echo signal in the parameter domain as follows:

[0146]

[0147] Among them, R' represents the equivalent double-base initial distance search value, v' represents the equivalent initial velocity search value, and α' represents the equivalent acceleration search value. After being processed by this method, the target energy completes coherent accumulation in the parameter domain, and the signal form is transformed from the time-frequency domain to the parameter domain.

[0148] The sea-based platform adopts KT-based algorithm to accumulate target energy within the node.

[0149] The third echo signal of the range frequency corresponding to the received echo after the range compression of the sea-based platform is expressed as:

[0150]

[0151] Among them, σ sea represents the target scattering coefficient of the sea-based node, f r Represents the frequency variable in the distance frequency domain, R sea represents the equivalent dual-base initial distance between the sea-based receiving platform and the target, v sea is the equivalent radial velocity between the sea-based receiving platform and the target, α sea Represents the equivalent radial acceleration between the airborne receiving platform and the target.

[0152] Performing the traditional KT transform on the signal, the corrected echo signal is expressed as:

[0153]

[0154] The matched filter function is constructed as follows:

[0155]

[0156] This function is used to compensate for the velocity fuzzy factor and acceleration. When the search value matches the true value, we get:

[0157]

[0158] Transforming the result to the distance time domain, we can get:

[0159]

[0160] Performing FFT along slow time gives:

[0161]

[0162] Therefore, when traversing the parameter search space of velocity ambiguity factor and acceleration, the coherent accumulation energy of the target echo signal reaches a peak value when the search value matches the true value.

[0163] At this time, the peak extraction technology can be used to estimate the unambiguous speed of the target, and the actual speed of the sea-based node target echo can be estimated as follows based on the searched speed ambiguity factor:

[0164]

[0165] S104, roughly estimate the coherent accumulation results within the nodes corresponding to each base platform, and build a graph node set of the platform dual base based on the rough estimation results; and use the voting accumulation method to screen the graph node set to obtain the maximum value of the graph node set; determine the optimal estimation node corresponding to the optimal accumulation node based on the maximum value; wherein, a low threshold method is used to roughly estimate the coherent accumulation results within the nodes corresponding to each base platform.

[0166] Specifically, when performing coarse threshold detection, the amplitude mean Z is calculated using the time-frequency domain or transform domain accumulation results, and the product of Z and the threshold factor K0 is used as a fixed threshold for screening local maximum points.

[0167]

[0168] All the above local maximum points are used to construct the graph node set Θ of the corresponding receiving platform.

[0169] Furthermore, the node coherence accumulation results of the airborne receiving platform are subjected to coarse threshold detection, and the graph node set is constructed by combining the parameter estimation results of velocity and acceleration. Used to characterize the rough estimation results accumulated over a long period of time by air-based platforms.

[0170] Furthermore, a coarse threshold detection is performed on the node coherent accumulation results of the land-based receiving platform, and the graph node set Characterize the rough estimate results of long-term accumulation for land-based platforms.

[0171] Furthermore, the node coherent accumulation results of the sea-based receiving platform are subjected to coarse threshold detection, and the parameter estimation results of velocity and acceleration are combined to use the graph node set Rough estimates used to characterize long-term accumulation on land-based platforms.

[0172] like Figure 3 The figure shows a schematic diagram of the node link transmission. Now define Ω∈{Θ α vΘ β ∪Θ χ} is the union of the rough threshold detection estimation results of the three heterogeneous platform nodes, where Θ α , Θ β , Θ χ As a subset, it contains several mutually communicating nodes used to represent rough estimation results. There is a unique effective communication link between the subset. There is at least one direct or indirect information path between any two nodes in the subset. The information of two adjacent subsets is interoperable, but the data link transmission across subsets must pass through the subset level.

[0173] To address this phenomenon, the maximum value screening problem is transformed into a voting accumulation problem between nodes. First, a voting matrix Y is established for all possible accumulation values. m,n,q , whose size is designed to be M×N×Q, where M is the graph node set Θ α The number of internal nodes, N represents the graph node set Θ β The number of internal nodes, Q represents the graph node set Θ χ The number of internal nodes. Then all voting results of the voting matrix are expressed as:

[0174] Y m,n,q =Θ α (A air ) m +Θ β (A ground ) n +Θ χ (A sea ) q (43)

[0175] After discrete voting for all possible accumulation values. Since the voting value is an important parameter reflecting the true distance value of the target, the larger the voting value of the accumulation unit, the greater the probability of its corresponding true distance value of the target. On the contrary, the smaller the accumulation value, the smaller the probability of its corresponding target distance value. Therefore, the position estimate corresponding to the optimal accumulation node of the graph node set is expressed as:

[0176]

[0177] Among them, Y m,n,q represents the voting result; m represents the number of nodes in the first set of the graph node set; n represents the number of nodes in the second set of the graph node set; q represents the number of nodes in the third set of the graph node set; argmax{·} represents the maximum value function; Represents the optimal estimated node after voting accumulation of the three subsets.

[0178] S105, constructing a compensation function corresponding to each base platform in the heterogeneous receiving platform according to the optimal estimation node, and using the compensation function to compensate the first frequency domain echo signal corresponding to each base platform, performing non-coherent accumulation on each base platform to obtain a non-coherent accumulation result, and completing the signal-level weak target energy accumulation of multiple base heterogeneous platforms.

[0179] Specifically, in step S105, a compensation function corresponding to each base platform in the heterogeneous receiving platform is constructed according to the optimal estimation node, and the first frequency domain echo signal corresponding to each base platform is compensated by using the compensation function, including:

[0180] (1) Determine the optimal estimation parameters of each base platform in the heterogeneous receiving platform according to the optimal estimation node;

[0181] (2) determining a parameter compensation function corresponding to each base platform according to the optimal estimated parameter, and using the parameter compensation function corresponding to each base platform to compensate the first frequency domain echo signal corresponding to each base platform to obtain a first compensation signal corresponding to each base platform;

[0182] (3) Determine the reference node of each base platform, and construct the compensation function based on the parameter differences corresponding to the remaining base platforms according to the reference node and the optimal estimation node.

[0183] Exemplarily, the optimal estimation parameters corresponding to each node are obtained using the optimal estimation node Three parameter compensation functions are constructed as follows:

[0184]

[0185] use Eliminating the speed and acceleration differences within the node, the signals after parameter compensation for each heterogeneous platform are:

[0186]

[0187] It can be seen from the above formula that the Doppler influence of each node has been eliminated, but there are differences in envelope positions, and non-coherent accumulation between nodes needs to be completed.

[0188] For the optimal estimation node, first select the reference node, and then construct the parameter difference compensation function. Perform time-frequency domain correction on the original echoes of the air-based, land-based, and sea-based signals in the time-frequency domain respectively, and perform non-coherent accumulation on the corrected signals of the three nodes, and finally obtain the maximum value after non-coherent accumulation.

[0189] In this embodiment, an airborne node is selected as a directional reference node for signal level energy enhancement, and the following distance correction function is constructed:

[0190]

[0191] The distance difference between the land-based node and the air-based node is expressed as The distance difference between the sea-based node and the air-based node is expressed as

[0192] Specifically, in step S105, non-coherent accumulation is performed on each base platform to obtain a non-coherent accumulation result, and the signal-level weak target energy accumulation of multiple base heterogeneous platforms is completed, including:

[0193] (1) constructing a compensation function according to the parameter difference to correct the first frequency domain echo signal corresponding to each base platform to obtain a correction signal corresponding to each base platform;

[0194] (2) Using the correction signals corresponding to each base platform, non-coherent accumulation is performed on each base platform to obtain non-coherent accumulation results, thus completing the signal-level weak target energy accumulation of multiple heterogeneous platforms.

[0195] Here, the non-coherent accumulation result is expressed as:

[0196]

[0197] Among them, f r represents the distance frequency domain variable; t m represents a slow time variable; Indicates the signal after compensation of the air-based platform; represents the distance difference compensation function of the land-based platform; Indicates the signal after compensation of the land-based platform; Indicates the signal after compensation of the sea-based platform; represents the distance difference compensation function of the sea-based platform; t n represents the fast time variable; f m represents the pulse-dimensional frequency domain variable.

[0198] Exemplarily, after the distance alignment processing of the proposed method, the three-node echoes realize signal-level non-coherent accumulation in the time-frequency domain, and the signal accumulation energy is the sum of the peak values ​​of multiple stations, which effectively improves the target detection capability.

[0199] The present invention is mainly verified by simulation experiment, and all steps and conclusions are verified to be correct on Matlab 2022b. The beneficial results of the present invention are further described in detail below in combination with the simulation configuration parameters shown in Table 1 and Table 2.

[0200] (I) Simulation experiment conditions

[0201] The simulation parameters of the radar system set in this experiment are shown in Table 1. It should be noted that, for the convenience of description, receiving station 1 refers to the receiving node of the air-based platform, receiving station 2 refers to the receiving node of the land-based platform, and receiving station 3 refers to the receiving node of the sea-based platform.

[0202] Table 1 Radar system simulation parameters

[0203] System Parameters Numeric System Parameters Numeric Carrier frequency 1.2GHz Receiving station 1 received echo signal-to-noise ratio -13dB bandwidth 2MHz Receiving station 2 received echo signal-to-noise ratio -20dB Pulse repetition frequency 1000 Receiving station 3 received echo signal-to-noise ratio -15dB Pulse Width 50us Sampling rate 4MHz Pulse accumulation number 1000

[0204] Table 2 gives the initial position, velocity and acceleration configuration information of the irradiation source satellite, three heterogeneous receiving nodes and the moving target in the 3D rectangular coordinate system in this simulation experiment.

[0205] Table 2 Motion parameters

[0206] Configuration parameters Numeric Satellite location of the source of illumination [-100e3, -100e3, 3.6e7]m Source satellite speed [10, 10, 10] m / s Receiving station 1 starting position [60e3,100e3,22e3]m Receiving station 1 speed [200, 300, -50] m / s Receiving station 1 acceleration <![CDATA[[20,15,30]m / s 2 ]]> Receiving station 2 starting position [10e3,10e3,500]m Receiving station 2 speed [[0,0,0]m / s Receiving station 2 acceleration <![CDATA[[0,0,0]m / s 2 ]]> Receiving station 3 starting position [80e3,4e3,0]m Receiving station 3 speed [4, 5, 0] m / s Receiving station 3 acceleration <![CDATA[[0,0,1]m / s 2 ]]> Target initial position 150e3,150e3,10e3]m Target speed [-800, -600, -500]m / s Target acceleration <![CDATA[[-20,-20,0]m / s 2 ]]>

[0207] (II) Simulation experiment content and result analysis

[0208] The embodiment of the present invention constructs a multi-base heterogeneous platform receiving echo data under a one-transmit-multiple-receive system based on a signal model. In the first step, the long-term accumulation algorithm described in the present invention is used to select a strategy distribution to perform intra-node coherent accumulation on the three heterogeneous platforms, and a compensation function is constructed according to the first-level accumulation result, and then the second-level non-coherent accumulation between nodes is completed, finally achieving weak target energy enhancement and detection.

[0209] Figure 4a A diagram showing the result of receiving echo range compression signals from an air-based platform; Figure 4b It represents the result diagram of echo range compression signal received by land-based platform; Figure 4c The figure shows the result of receiving echo range compression signal from the sea-based platform. The horizontal axis represents the number of pulses and the vertical axis represents the distance unit. Figure 4a , Figure 4b and Figure 4c It can be seen that for high-speed maneuvering weak targets, due to the large differences in the viewing angles of the three heterogeneous platforms and the certain maneuverability of the air-based platform itself, the projection in the radial direction shows a large equivalent velocity and acceleration. Therefore, the target trajectory spans 70 distance units in the air-based receiving echo, and there is a relatively obvious range bending phenomenon. The echoes of land-based and sea-based receiving platforms are mainly first-order range migration or range movement. In addition, according to the geometric configuration, the land-based node layout is usually far away from the target at a horizontal straight-line distance. Figure 4a , Figure 4b , Figure 4cIt can also be found that the target starts at a dual-base distance of 116km in the air-based reception echo, starts at a dual-base distance of 190km in the land-based reception echo, and starts at a dual-base distance of 153km in the sea-based reception echo. The equivalent initial distance of the dual-base distance history of the land-based node is far greater than the other two initial distances, which is consistent with the geometric structure analysis.

[0210] Figure 5a Given the accumulated results after compensation of the airborne receiving platform parameters, Figure 5b Given the accumulated results after compensation of the airborne receiving platform parameters, Figure 5c The accumulated results after the sea-based receiving platform parameter compensation are given. In the embodiment of the present invention, the air-based platform receiving node, i.e., receiving station 1, is selected as the reference node, and the target parameter positions of other nodes will be close to the reference node. Figure 5d It can be seen that the non-coherent accumulation results are specifically manifested in that the time-frequency domain distance and Doppler envelope position are aligned with the reference node, the peak level is significantly improved, and the noise around the peak is more stable than the reference node, which achieves the enhancement of weak echo signals and can be used for effective detection of weak targets.

[0211] Furthermore, the embodiment of the present invention provides a comparison of the computational complexity of the disclosed method and the algorithm proposed by MIMO-GRFT. Assume that the number of receiving platforms is set to 3, the number of acceleration searches, the number of speed searches, the number of distance searches, the number of distance units, and the number of pulse accumulations are N respectively. a 、N v 、N r , N and M.

[0212] The computational complexity of the nodes of the air-based receiving platform in the embodiment of the present invention is expressed as:

[0213] O[(K1+1)NMlog2N+(K1+K2+7)NM+4NMlog2M+(K1+K2)Mlog2M];

[0214] The computational complexity of the algorithm used for the land-based receiving platform is:

[0215] O(N v N a NM);

[0216] The computational complexity of the long-term coherent integration algorithm in the sea-based receiving platform node is:

[0217] O[(K1+4)NM+(N a +K1+4)NMlog2M];

[0218] The freight complexity of non-coherent accumulation between heterogeneous nodes is expressed as O(4NM), so the total computational complexity is:

[0219]

[0220] During the accumulation process of the MIMO-GRFT algorithm, the target trajectory within the node needs to be searched in three dimensions: distance, speed, and acceleration. The computational complexity is: O(3N v N a NM); the computational complexity accumulated between nodes is simplified as: O(4NM)O(4NM), so the total computational complexity of this method can be expressed as: O(3N v N a NM+4NM).

[0221] Table 3 shows the time complexity comparison under the simulation conditions of the embodiment, and the simulation experiment conditions are 64GB RAM and matlab 2022b version. The running time of the method disclosed in the present invention is 217.21s, and the running time of the MIMO-GRFT method is 349.18s. Therefore, the proposed algorithm significantly reduces the time overhead while completing the signal-level target capability accumulation of the multi-base heterogeneous platform.

[0222] Table 3 Algorithm running time comparison

[0223] Comparison Method Run time Proposed Algorithm 217.21s MIMO-GRFT 349.18s

[0224] The above simulation experiments also verify the effectiveness and reliability of the method proposed in the present invention.

[0225] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. All or part of the present invention can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, mobile communication terminals, multi-processor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0226] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the present invention.

Claims

1. A weak target energy accumulation strategy and method for a multi-base heterogeneous platform, characterized in that: include: Constructing a dual-base distance history mathematical model of a heterogeneous receiving platform, and obtaining a dual-base distance history expression of the dual-base distance history according to the dual-base distance history mathematical model; Acquire target echo signals corresponding to the plurality of heterogeneous receiving platforms, perform matched filtering on the target echo signals, and obtain range-compressed echo signals; perform the following processing on the range-compressed echo signals corresponding to each of the heterogeneous receiving platforms: Combining the distance-compressed echo signal with the dual-base distance history expression to obtain a first echo signal; wherein the heterogeneous receiving platform includes: an air-based platform, a land-based platform, and a sea-based platform; Using different algorithms for different base platforms in the heterogeneous receiving platform to perform intra-node target energy accumulation calculation on the first echo signal, so as to obtain the first frequency domain echo signal corresponding to each base platform and the intra-node coherent accumulation result; A low threshold method is used to roughly estimate the coherent accumulation results within the nodes corresponding to each base platform, and a graph node set of the platform dual base is constructed based on the rough estimation results; and the graph node set is screened using a voting accumulation method to obtain the maximum value of the graph node set; and the optimal estimation node corresponding to the optimal accumulation node is determined based on the maximum value; A compensation function corresponding to each base platform in the heterogeneous receiving platform is constructed according to the optimal estimation node, and the first frequency domain echo signal corresponding to each base platform is compensated by using the compensation function, and non-coherent accumulation is performed on each base platform according to the compensated signal to obtain a non-coherent accumulation result, thereby completing the signal-level weak target energy accumulation of multiple base heterogeneous platforms.

2. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 1, characterized in that: The dual-base distance history mathematical model is expressed as: R(t m )=||R TP (t m )||+||R RP (t m )||-||R TR (t m )||; Among them, R TP (t m ) represents the distance history between the irradiation source satellite and the target; R TR (t m ) represents the distance history between the illumination source satellite and the multi-base heterogeneous receiving platform; R RP (t m ) represents the distance history between the multi-base heterogeneous receiving platform and the target; ‖·‖ represents the Euclidean norm of the vector.

3. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 1, characterized in that: The acquiring target echo signals corresponding to the plurality of heterogeneous receiving platforms and performing matched filtering processing on the target echo signals to obtain range-compressed echo signals includes: Determine the transmission signal emitted by the irradiation source satellite to the ground; According to the dual-base distance relationship, target echo signals corresponding to the plurality of heterogeneous receiving platforms are acquired; The target echo signal and the direct wave are cross-correlated to obtain range-compressed echo signals corresponding to the plurality of heterogeneous receiving platforms.

4. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 1, characterized in that: The echo signal of the range compression is expressed as: Among them, A i represents the signal amplitude after pulse compression of the i-th receiving platform; B represents the signal bandwidth; R TP (t m ) represents the distance history between the irradiation source satellite and the target; R RP,i (t m ) represents the distance history between the multi-base heterogeneous receiving platform and the target; R TR,i (t m ) represents the distance history between the irradiation source satellite and the multi-base heterogeneous receiving platforms.

5. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 1, characterized in that: The first echo signal is expressed as: Among them, A i represents the signal amplitude after pulse compression of the i-th receiving platform; B represents the signal bandwidth; t n Indicates fast time; t m Indicates slow time; R 0,i represents the equivalent dual-base initial distance between the i-th receiving platform and the target; v i represents the equivalent radial velocity between the i-th receiving platform and the target; a i represents the equivalent radial acceleration between the i-th receiving platform and the target; c represents the speed of light; λ represents the carrier wavelength.

6. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 1, characterized in that: The using different algorithms for different base platforms in the heterogeneous receiving platform to perform accumulation calculation of target energy within the node on the first echo signal includes: The air-based platform adopts a TRT-based algorithm to achieve target energy accumulation within the node; The land-based platform adopts GRFT-based algorithm to achieve target energy accumulation within the node; The sea-based platform adopts a KT-based algorithm to achieve target energy accumulation within the node.

7. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 1, characterized in that: The constructing, according to the optimal estimation node, a compensation function corresponding to each base platform in the heterogeneous receiving platform, and using the compensation function to compensate the first frequency domain echo signal corresponding to each base platform includes: Determining optimal estimation parameters of each base platform in the heterogeneous receiving platform according to the optimal estimation node; Determine a parameter compensation function corresponding to each base platform according to the optimal estimated parameter, and use the parameter compensation function corresponding to each base platform to compensate the first frequency domain echo signal corresponding to each base platform to obtain a first compensation signal corresponding to each base platform; The reference node of each base platform is determined, and a compensation function is constructed based on the parameter differences corresponding to the remaining base platforms according to the reference node and the optimal estimation node.

8. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 7, characterized in that: The non-coherent accumulation is performed on each base platform to obtain a non-coherent accumulation result, and the signal-level weak target energy accumulation of the multi-base heterogeneous platform is completed, including: Constructing a compensation function according to the parameter difference to correct the first frequency domain echo signal corresponding to each base platform to obtain a correction signal corresponding to each base platform; By utilizing the correction signals corresponding to the base platforms, non-coherent accumulation is performed on each base platform to obtain a non-coherent accumulation result, thereby completing the signal-level weak target energy accumulation of multiple base heterogeneous platforms.

9. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 1, characterized in that: The optimal estimation node is expressed as: Among them, Y m,n,q represents the voting result; m represents the number of nodes in the first set of the graph node set; n represents the number of nodes in the second set of the graph node set; q represents the number of nodes in the third set of the graph node set; argmax{·} represents the maximum value function.

10. The weak target energy accumulation strategy and method for a multi-base heterogeneous platform according to claim 1, characterized in that: The non-coherent accumulation result is expressed as: Among them, f r represents the distance frequency domain variable; t m represents a slow time variable; Indicates the signal after compensation of the air-based platform; represents the distance difference compensation function of the land-based platform; Indicates the signal after compensation of the land-based platform; Indicates the signal after compensation of the sea-based platform; represents the distance difference compensation function of the sea-based platform; t n represents the fast time variable; f m represents the pulse-dimensional frequency domain variable.

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