FDA-MIMO radar system space topology and transmit-receive parameter optimization method

Abstract

The invention discloses an FDA-MIMO radar system space topology and transmit-receive parameter optimization method. The method is specifically implemented according to the following steps: step 1, establishing a distributed FDA-MIMO radar system basic model; and step 2, establishing a distributed FDA-MIMO radar system optimization model, and realizing site configuration. The problems that an existing radar system is poor in target signal receiving capacity and low in radar detection performance are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar, and specifically relates to a method for optimizing the spatial topology and transceiver parameters of an FDA-MIMO radar system. Background Art

[0002] In modern warfare, electronic warfare and signal interference are common tactical means. As a key technology for detecting and tracking airborne targets, the performance of a radar system directly affects the strength of air defense and anti-missile capabilities. With the rapid development of electronic technology, traditional centralized radar systems have been difficult to meet the requirements of modern warfare for the flexibility, concealment, and anti-interference capabilities of radar systems. Therefore, distributed radar systems have emerged. By dispersing multiple radar nodes, the anti-damage ability and detection accuracy of the system can be improved. The core advantages of distributed radar systems lie in their flexibility and scalability. By deploying radar nodes at different positions, omnidirectional coverage of targets can be achieved, thereby improving the reliability and accuracy of detection.

[0003] The FDA-MIMO radar system is a new type of radar system that realizes beamforming and target detection by introducing frequency steps in the transmitting and receiving arrays. Compared with traditional phased array radars, this system has higher spatial resolution and flexibility. However, the FDA-MIMO radar system faces problems such as high signal processing complexity and great difficulty in system configuration optimization in practical applications. Especially in the scenario of distributed deployment, how to reasonably plan the spatial positions and transceiver parameters of radar nodes to achieve the best detection performance is a current research hotspot and difficulty. Existing technical solutions mainly rely on experience or simple optimization algorithms. These methods often cannot globally optimize the performance of the radar system and are difficult to adapt to complex and changeable battlefield environments in practical applications, resulting in poor target signal reception ability and low radar detection performance. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for optimizing the spatial topology and transceiver parameters of an FDA-MIMO radar system, which solves the problems of poor target signal reception ability and low radar detection performance of existing radar systems.

[0005] The technical solution adopted by the present invention is that the method for optimizing the spatial topology and transceiver parameters of an FDA-MIMO radar system is specifically implemented according to the following steps:

[0006] Step 1, establish a basic model of a distributed FDA-MIMO radar system;

[0007] Step 2, establish an optimization model of a distributed FDA-MIMO radar system to realize site configuration.

[0008] The characteristics of the present invention also lie in that

[0009] Step 1.1. In the distributed FDA-MIMO system, configure the distributed FDA-MIMO radar system according to the number of radar transmitters and receivers.

[0010] Step 1.2. Establish a signal model for the distributed FDA-MIMO radar system configured in Step 1.1.

[0011] Step 1.1.1. Configure a two-transmitter and three-receiver configuration.

[0012] Step 1.1.2. Configure a four-transmitter and four-receiver configuration.

[0013] In the distributed FDA-MIMO system, three radars are used. When the number of transmitting radars is P (P = 2), the number of receiving radars is Q (Q = 3), and the corresponding number of radar nodes is I (I = 3). Among them, the transmitting and receiving radars of two radars are co-located FDA-MIMO radars with self-transmitting and self-receiving, and the number of transmitting and receiving array elements are M and N respectively. The remaining third radar is a phased array radar that only receives passively.

[0014] In the distributed FDA-MIMO system, four radars are used. When the number of transmitting radars is P (P = 4), the number of receiving radars is Q (Q = 4), and the corresponding number of radar nodes is I (I = 4). The transmitting and receiving radars of the four radars are co-located FDA-MIMO radars with self-transmitting and self-receiving, and the number of transmitting and receiving array elements are M and N respectively.

[0015] Step 1.2.1. Assume that there is a point target in the far field of space located at the origin. The target space coordinates relative to the i-th (i = 1, 2,..., I) radar site are (θ i , R i ), where θ i represents the angle between the target and the i-th radar site, and R i represents the distance between the target and the i-th radar site.

[0016] Assume that the first array element of the array is the reference coordinate of the corresponding site, the distance between array elements is d, and a very small frequency step Δf is introduced between the transmitting radar array elements. The frequency step is much smaller than the carrier frequency.

[0017] The signal transmitted by the p-th (p = 1, 2,..., P, P ≤ I) radar is received by the q-th (q = 1, 2,..., Q, Q ≤ I) radar, and the signal-to-interference-plus-noise ratio (SINR) obtained after matched filter signal processing is SINR pq ;

[0018]

[0019] In formula (1), is the desired signal power, is the noise variance; w pq is the reception weight vector received by the q-th radar (q = 1, 2,..., Q) when the p-th radar (p = 1, 2,..., P) transmits; u A is the actual virtual steering vector of the target; Σ pq (Δf) is the covariance matrix of clutter between the p-th radar (p = 1, 2,..., P) and the q-th radar (q = 1, 2,..., Q); represents the transpose operation, ||·|| 2 represents the square of the norm;

[0020] Step 1.2.2, in the radar configuration of two transmitters and three receivers in Step 1.1.1, the signal-to-interference-plus-noise ratio (SINR) output by the receiving radar Q2 when the transmitting radar P1 transmits the signal is SINR 12 ; the signal-to-interference-plus-noise ratio (SINR) output by the receiving radar Q1 when the transmitting radar P2 transmits the signal is SINR 21 ; therefore, in the radar configuration of two transmitters and three receivers, the overall output signal-to-interference-plus-noise ratio of the system needs to subtract SINR 12 and SINR 21 :

[0021]

[0022] Step 1.2.3, in the radar configuration of four transmitters and four receivers in Step 1.1.2, at this time P = Q = I, the overall output signal-to-interference-plus-noise ratio of the system is:

[0023]

[0024] Step 1.2.1.1, calculate the actual virtual steering vector u of the target in formula (1) A as;

[0025]

[0026] In formula (2), b(θ q ) is the reception steering vector of the q-th radar (q = 1, 2,..., Q), a(θ p , R p , R q ) is the transmission steering vector of the p-th radar (p = 1, 2,..., P);

[0027] Calculate the reception steering vector b(θ of the q-th radar (q = 1, 2,..., Q) in formula (2) q );

[0028]

[0029] In formula (3), λ0 is the reference element wavelength, and H is the conjugate matrix;

[0030] Calculate the transmit steering vector a(θ p ,R p ,R q ) of the p-th (p = 1, 2, …, P) radar in formula (2);

[0031]

[0032] In formula (4), a R (R p ,R q ) is the steering vector of distance R, a θ (θ p ) is the steering vector of angle θ, ⊙ represents the Hadamard product, and calculate the steering vector of distance R and the steering vector of angle θ in formula (4);

[0033]

[0034] Step 1.2.2.2, calculate the clutter covariance matrix Σ pq (Δf) between the p-th (p = 1, 2, …, P) radar and the q-th (q = 1, 2, …, Q) radar in formula (1);

[0035]

[0036] Among them, represents the clutter noise variance between the p-th radar and the q-th radar; represents the channel response matrix at a specific angle time delay and frequency offset Δf;

[0037] The signal-to-interference-plus-noise ratio accumulation of the radar system output in formula (1) is SINR o ;

[0038]

[0039] Step 2.1, in order to maximize the output signal-to-interference-plus-noise ratio, construct an optimization model for a distributed FDA-MIMO radar system, and the optimization problem is:

[0040]

[0041] In formula (11), Ω i is the set of feasible positions of the i-th (i = 1, 2, …, I) radar, and the feasible deployment area is modeled as a convex set;

[0042] Step 2.2. Transform the integer programming problem in formula (11), which is a multi-dimensional NP-hard problem, and solve it using a multi-start greedy search algorithm. Select the optimal radar site location. Start the search from multiple initial points. During each search process, select the site that can minimize the objective function under the condition of meeting the constraints as the alternative solution until the number of sites meets the requirements.

[0043] Specifically, Step 2.2 is as follows:

[0044] Step 2.2.1. Initialize variables. For Let r sn = 1;

[0045] Step 2.2.2. Traverse the transmitting array elements and select the transmitting array element that minimizes the objective function.

[0046] Step 2.2.3. Repeat Step 2.2.2 until the number of selected transmitting array elements is reached;

[0047] Step 2.2.4. Fix the transmitting array elements, traverse the receiving array elements, and select the receiving array element that minimizes the objective function.

[0048] Step 2.2.5. Repeat Step 2.2.5 until the number of selected transmitting array elements is reached.

[0049] The beneficial effects of the present invention are as follows. The method for optimizing the spatial topology and transceiver parameters of the FDA-MIMO radar system of the present invention establishes a signal model and an optimization model by adjusting the weight vectors of transmission and reception, and solves three sub-problems of frequency offset optimization, weight vector optimization, and site location optimization by using a multi-start greedy search (MSLS) algorithm, thereby significantly improving the SINR and tracking accuracy of the radar system. The present invention not only improves the detection performance of the radar system, but also enhances the adaptability and flexibility of the system, effectively reduces the influence of external interference on the performance of the radar system, and can better meet the requirements of modern warfare. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a schematic diagram of the two-transmitter and three-receiver configuration of the present invention;

[0051] Figure 2 is a schematic diagram of the four-transmitter and four-receiver configuration of the present invention;

[0052] Figure 3 is a geometric relationship diagram of the target and the alternative site positions in Scenario 1 of the present invention;

[0053] Figure 4 is a SINR diagram obtained by two site configuration algorithms in Scenario 1 of the present invention;

[0054] Figure 5It is a geometric relationship diagram of the target and the alternative positions of the site in Scenario 2 of the present invention;

[0055] Figure 6 It is the SINR diagram obtained by two site configuration algorithms in Scenario 2 of the present invention. Detailed implementation manners

[0056] The present invention will be described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0057] Embodiment 1

[0058] The method for optimizing the spatial topology and transceiver parameters of the FDA-MIMO radar system of the present invention is specifically implemented according to the following steps:

[0059] Step 1, establish a basic model of the distributed FDA-MIMO radar system;

[0060] Step 2, establish an optimization model of the distributed FDA-MIMO radar system to achieve site configuration.

[0061] Embodiment 2

[0062] On the basis of Embodiment 1, Step 1 of this embodiment is specifically

[0063] Step 1.1, in the distributed FDA-MIMO system, configure the distributed FDA-MIMO radar system according to the number of radar transmitters and receivers;

[0064] Step 1.1.1, configure a two-transmitter and three-receiver configuration;

[0065] In the distributed FDA-MIMO system, three radars are used. When the number of transmitting radars is P (P = 2), and the number of receiving radars is Q (Q = 3), the corresponding number of radar nodes is I (I = 3). Among them, the transmitting and receiving radars of two radars are co-located FDA-MIMO radars with self-transmitting and self-receiving, and the number of transmitting and receiving array elements is M and N respectively. The remaining third radar is a phased array radar that only receives passively.

[0066] Step 1.1.2, configure a four-transmitter and four-receiver configuration;

[0067] In the distributed FDA-MIMO system, four radars are used. When the number of transmitting radars is P (P = 4), and the number of receiving radars is Q (Q = 4), the corresponding number of radar nodes is I (I = 4). The transmitting and receiving radars of the four radars are co-located FDA-MIMO radars with self-transmitting and self-receiving, and the number of transmitting and receiving array elements is M and N respectively.

[0068] Step 1.2, establish a signal model for the distributed FDA-MIMO radar system configuration in Step 1.1.

[0069] Step 1.2.1, assume that there is a point target in the far field of space located at the origin of coordinates. The target space coordinates relative to the i-th (i = 1, 2,..., I) radar station are (θ i , R i ), where θ i represents the angle between the target and the i-th radar station, and R i represents the distance between the target and the i-th radar station;

[0070] Assume that the first array element is the reference coordinate of the corresponding station, the distance between array elements is d, and a very small frequency step Δf is introduced between the transmitting radar array elements. The frequency step is much smaller than the carrier frequency;

[0071] The signal transmitted by the p-th (p = 1, 2,..., P, P ≤ I) radar is received by the q-th (q = 1, 2,..., Q, Q ≤ I) radar, and the signal-to-interference-plus-noise ratio obtained after matched filter signal processing is SINR pq ;

[0072]

[0073] In formula (1), σ s 2 is the desired signal power, is the noise variance; w pq is the receiving weight vector received by the q-th (q = 1, 2,..., Q) radar when the p-th (p = 1, 2,..., P) radar transmits; u A is the actual virtual steering vector of the target; Σ pq (Δf) is the covariance matrix of the clutter between the p-th (p = 1, 2,..., P) radar and the q-th (q = 1, 2,..., Q) radar; represents the transpose operation, ||·|| 2 represents the square of the norm;

[0074] Step 1.2.1.1, calculate the actual virtual steering vector u of the target in formula (1) A as;

[0075]

[0076] In formula (2), b(θ q ) is the receiving steering vector of the q-th (q = 1, 2,..., Q) radar, and a(θ p , R p , R q ) is the transmitting steering vector of the p-th (p = 1, 2,..., P) radar;

[0077] Calculate the receiving steering vector b(θ of the q-th (q = 1, 2,..., Q) radar in formula (2)q );

[0078]

[0079] In formula (3), λ0 is the reference element wavelength, and H is the conjugate matrix;

[0080] Calculate the transmit steering vector a(θ of the p-th (p = 1, 2,..., P) radar in formula (2) p , R p , R q );

[0081]

[0082] In formula (4), a R (R p , R q ) is the steering vector at distance R, a θ (θ p ) is the steering vector at angle θ. ⊙ represents the Hadamard product. Calculate the steering vector at distance R and the steering vector at angle θ in formula (4);

[0083]

[0084] Step 1.2.2.2, calculate the covariance matrix Σ of the clutter between the p-th (p = 1, 2,..., P) radar and the q-th (q = 1, 2,..., Q) radar in formula (1) pq (Δf);

[0085]

[0086] Where, represents the clutter noise variance between the p-th radar and the q-th radar; represents the channel response matrix at a specific angle time delay and frequency offset Δf;

[0087] The sum of the signal-to-interference-plus-noise ratios output by the radar system in formula (1) is SINR o ;

[0088]

[0089] Step 1.2.2, in the radar configuration of two transmitters and three receivers in Step 1.1.1, the signal-to-interference-plus-noise ratio output when the transmitting radar P1 transmits a signal and the receiving radar Q2 receives the signal is SINR 12 ; The signal-to-interference-plus-noise ratio output when the transmitting radar P2 transmits a signal and the receiving radar Q1 receives the signal is SINR 21; Therefore, in the radar configuration of two transmitters and three receivers, the overall system output signal-to-interference-plus-noise ratio accumulation needs to subtract SINR 12 and SINR 21 :

[0090]

[0091] Step 1.2.3, in the radar configuration of four transmitters and four receivers in Step 1.1.2, at this time P = Q = I, the overall system output signal-to-interference-plus-noise ratio is:

[0092]

[0093] Embodiment 3

[0094] Based on Embodiment 2, Step 2 of this embodiment is specifically as follows;

[0095] Step 2.1, in order to maximize the output signal-to-interference-plus-noise ratio, construct an optimization model for the distributed FDA-MIMO radar system, and the optimization problem is:

[0096]

[0097] In formula (11), Ω i is the set of feasible positions of the i-th (i = 1, 2,..., I) radar. The feasible deployment area is modeled as a convex set, such as a circle.

[0098] Step 2.2, convert the integer programming problem of formula (11), which is a multi-dimensional NP-hard problem, and use the multi-start local search algorithm (MSLS) to solve it. Select the optimal radar site location. Start searching from multiple initial points. In each search process, select the site that can minimize the objective function as the alternative solution under the condition of meeting the constraints until the number of sites meets the requirements.

[0099] Embodiment 4

[0100] The method for optimizing the spatial topology and transceiver parameters of the FDA-MIMO radar system of the present invention is specifically implemented according to the following steps:

[0101] Step 1, establish a basic model of the distributed FDA-MIMO radar system;

[0102] Step 1.1, in the distributed FDA-MIMO system, configure the distributed FDA-MIMO radar system according to the number of radar transmitters and receivers;

[0103] Step 1.1.1, configure the two transmitters and three receivers configuration;

[0104] Such as Figure 1As shown in the figure, three radars are used in the distributed FDA-MIMO system. When the number of transmitting radars is P (P = 2), the number of receiving radars is Q (Q = 3), and the corresponding number of radar nodes is I (I = 3). Among them, the transmitting and receiving radars of two radars are co-located FDA-MIMO radars with self-transmitting and self-receiving, and the number of transmitting and receiving array elements are M and N respectively. The remaining third radar is a phased array radar that only receives passively.

[0105] Step 1.1.2, perform a four-transmit and four-receive configuration;

[0106] As Figure 2 shown in the figure, four radars are used in the distributed FDA-MIMO system. When the number of transmitting radars is P (P = 4), the number of receiving radars is Q (Q = 4), and the corresponding number of radar nodes is I (I = 4). The transmitting and receiving radars of the four radars are co-located FDA-MIMO radars with self-transmitting and self-receiving, and the number of transmitting and receiving array elements are M and N respectively.

[0107] Step 1.2, establish a signal model for the distributed FDA-MIMO radar system configuration in Step 1.1.

[0108] Step 1.2.1, assume that there is a point target in the far field of space located at the origin. The target space coordinates relative to the i-th (i = 1, 2,..., I) radar site are (θ i , R i ), where θ i represents the angle between the target and the i-th radar site, and R i represents the distance between the target and the i-th radar site;

[0109] Assume that the first array element of the array is the reference coordinate of the corresponding site, the distance between array elements is d, and a very small frequency step Δf is introduced between the transmitting radar array elements. The frequency step is much smaller than the carrier frequency;

[0110] The signal transmitted by the p-th (p = 1, 2,..., P, P ≤ I) radar is received by the q-th (q = 1, 2,..., Q, Q ≤ I) radar, and the signal-to-interference-plus-noise ratio obtained after matched filter signal processing is SINR pq ;

[0111]

[0112] In formula (1), is the desired signal power, is the noise variance; w pq is the receiving weight vector when the p-th (p = 1, 2,..., P) radar transmits and the q-th (q = 1, 2,..., Q) radar receives; u A is the actual virtual steering vector of the target; Σ pq$(\Delta f)$ is the covariance matrix of clutter between the $p$-th ($p = 1, 2, \ldots, P$) radar and the $q$-th ($q = 1, 2, \ldots, Q$) radar; denotes the transpose operation, $\|\cdot\|$ 2 denotes the square of the norm;

[0113] Step 1.2.1.1, calculate the actual virtual steering vector $\mathbf{u}$ of the target in formula (1) A as;

[0114]

[0115] In formula (2), $\mathbf{b}(\theta$ q ) is the receiving steering vector of the $q$-th ($q = 1, 2, \ldots, Q$) radar, and $\mathbf{a}(\theta$ p , $R$ p , $R$ q ) is the transmitting steering vector of the $p$-th ($p = 1, 2, \ldots, P$) radar;

[0116] Calculate the receiving steering vector $\mathbf{b}(\theta$ q ) of the $q$-th ($q = 1, 2, \ldots, Q$) radar in formula (2);

[0117]

[0118] In formula (3), $\lambda_0$ is the reference element wavelength, and $H$ is the conjugate matrix;

[0119] Calculate the transmitting steering vector $\mathbf{a}(\theta$ p , $R$ p , $R$ q ) of the $p$-th ($p = 1, 2, \ldots, P$) radar in formula (2);

[0120]

[0121] In formula (4), $\mathbf{a}$ R ($R$ p , $R$ q ) is the steering vector of range $R$, and $\mathbf{a}$ θ ($\theta$ p ) is the steering vector of angle $\theta$, $\odot$ represents the Hadamard product, calculate the steering vector of range $R$ and the steering vector of angle $\theta$ in formula (4);

[0122]

[0123] Step 1.2.2.2, calculate the covariance matrix $\Sigma$ pq $(\Delta f)$ of clutter between the $p$-th ($p = 1, 2, \ldots, P$) radar and the $q$-th ($q = 1, 2, \ldots, Q$) radar in formula (1);

[0124]

[0125] Among them, represents the clutter noise variance between the p-th radar and the q-th radar; represents at a specific angle time delay and the channel response matrix at the frequency offset Δf;

[0126] The sum of the signal-to-interference-plus-noise ratios of the radar system output formula (1) is SINR o ;

[0127]

[0128] Step 1.2.2, in the radar configuration of two transmitters and three receivers in Step 1.1.1, the signal is transmitted by the transmitting radar P1, and the signal-to-interference-plus-noise ratio output by the receiving radar Q2 is SINR 12 ; The signal is transmitted by the transmitting radar P2, and the signal-to-interference-plus-noise ratio output by the receiving radar Q1 is SINR 21 ; Therefore, in the radar configuration of two transmitters and three receivers, the sum of the overall system output signal-to-interference-plus-noise ratio needs to subtract SINR 12 and SINR 21 :

[0129]

[0130] Step 1.2.3, in the radar configuration of four transmitters and four receivers in Step 1.1.2, at this time P = Q = I, the overall system output signal-to-interference-plus-noise ratio is:

[0131]

[0132] Step 2, establish an optimization model for the distributed FDA-MIMO radar system to achieve site configuration.

[0133] Step 2.1, in order to maximize the output signal-to-interference-plus-noise ratio, construct an optimization model for the distributed FDA-MIMO radar system, and the optimization problem is:

[0134]

[0135] In formula (11), Ω i is the set of feasible positions of the i-th (i = 1, 2,..., I) radar. The feasible deployment area is modeled as a convex set, such as a circle.

[0136] Step 2.2. The integer programming problem of formula (11), which is a multi-dimensional NP-hard problem, is solved by using the multi-start local search algorithm (MSLS). The optimal radar site location is selected. Starting from multiple initial points, during each search process, the site that can minimize the objective function is selected as an alternative solution under the condition of meeting the constraints until the number of sites meets the requirements.

[0137] Step 2.2.1. Initialize the variables. For let r sn = 1;

[0138] Step 2.2.2. Traverse the transmitting array elements and select the transmitting array element that minimizes the objective function.

[0139] Step 2.2.3. Repeat Step 2.2.2 until the number of selected transmitting array elements is reached;

[0140] Step 2.2.4. Fix the transmitting array elements, traverse the receiving array elements, and select the receiving array element that minimizes the objective function.

[0141] Step 2.2.5. Repeat Step 2.2.5 until the number of selected transmitting array elements is reached.

[0142] Embodiment 5

[0143] The present invention verifies the effectiveness of the proposed MSLS algorithm through simulation.

[0144] In the distributed FDA-MIMO radar, the system parameters are set as P tot = 10 6 W; τ c G t G r I p λ 2 / (L c L r ) = 0.01; λ = 0.3 m; The RCS of each target is constant, all being 1 m 2 ; M = 4 transmitting array elements, N = 8 receiving array elements, the element spacing is half wavelength, and the fixed frequency offset between elements is Δf = 25 kHz;.

[0145] After meshing the sites to be arranged, the following two scenarios are set respectively:

[0146] Scenario 1: And in the distributed MIMO radar, 2 transmitting sites achieve transceiver sharing, that is, a total of 3 sites need to be arranged.

[0147] Scenario 2: Moreover, all the transmitting stations of the distributed MIMO radar achieve transceiver sharing, that is, a total of 4 stations need to be arranged.

[0148] In addition to the proposed algorithm, a random site selection algorithm is introduced as a benchmark algorithm for comparison. In each simulation scenario, three batches of targets are set to fly. The tracking interval T s = 1 s, and the duration of each simulation K = 30 s.

[0149] The alternative positions of the stations in Scenario 1 and the geometric relationship of the three batches of targets are as Figure 3 shown, Figure 3 where the arrows in the figure indicate the target flight directions. The comparison of SINR obtained by the two station configuration algorithms is as Figure 4 shown. The SINR corresponds to the worst target. It can be seen that compared with the random site selection algorithm, the MSLS algorithm achieves a larger SINR. The station configuration results of the MSLS algorithm at three typical moments of k = 5, k = 15, and k = 25 are calculated respectively. The MSLS algorithm selects the position that can improve the accuracy of the target with the largest tracking error according to the geometric relationship between the target and the station to obtain higher energy efficiency.

[0150] Example 6

[0151] The alternative positions of the stations in Scenario 2 and the geometric relationship of the three batches of targets are as Figure 5 shown, and the arrows in the figure indicate the target flight directions. As Figure 6 shown, it is the comparison of the tracking accuracy obtained by the two station configuration algorithms. Compared with the random site selection algorithm, the MSLS algorithm achieves a larger SINR. The station configuration results of the MSLS algorithm at three typical moments of k = 5, k = 15, and k = 25 are calculated respectively. The MSLS algorithm selects the position that can improve the accuracy of the target with the largest tracking error according to the geometric relationship between the target and the station to obtain higher energy efficiency.

[0152] In the simulation experiment, compared with the traditional random site selection algorithm, the MSLS algorithm shows a significant improvement in tracking accuracy in different scenarios. This improvement not only enhances the radar system's ability to track fast-moving targets but also provides more reliable target information for precise strikes, thus having important application values in both military and civilian fields.

[0153] By optimizing the parameter configuration of radar nodes, the anti-jamming ability of the system is significantly enhanced. This enhancement of anti-jamming ability enables the radar system to maintain a stable working state and continue to provide accurate target information even under strong electronic jamming by the enemy. This is crucial for ensuring the continuous combat ability of the radar system in a high-threat environment and is also a major highlight of the present invention in improving the survivability and reliability of the radar system.

[0154] The method for optimizing the spatial topology and transceiver parameters of the FDA-MIMO radar system of the present invention realizes a significant improvement in the signal-to-interference-plus-noise ratio (SINR) of the distributed FDA-MIMO radar system. By precisely configuring the spatial layout and parameters of radar nodes, the receiving ability of the radar system for target signals is effectively enhanced, while the interference of background noise is reduced. In a complex battlefield environment, this optimization strategy enables the radar system to more clearly identify and track targets, improving the accuracy and reliability of target detection. A high SINR also means that the radar system can detect smaller targets at a farther distance, thereby expanding the surveillance range of the radar and improving the early warning ability; the multi-start greedy search (MSLS) algorithm adopted can dynamically adjust the configuration of radar nodes according to the geometric relationship between the target and the stations to achieve precise tracking of the target. By selecting the optimal positions of radar stations, the tracking accuracy of the target is greatly improved.

Claims

1. FDA-MIMO radar system spatial topology and transceiver parameter optimization method, characterized in that: Follow the steps below to implement it: Step 1, establish a basic model of distributed FDA-MIMO radar system; Step 2: Establish a distributed FDA-MIMO radar system optimization model to achieve site configuration.

2. The method for optimizing spatial topology and transceiver parameters of the FDA-MIMO radar system according to claim 1, characterized in that: In step 1, Step 1.1, in the distributed FDA-MIMO system, according to the number of radar transmitting and receiving, the distributed FDA-MIMO radar system is configured; Step 1.2, establish a signal model for the distributed FDA-MIMO radar system configuration in step 1.

1.

3. The method for optimizing spatial topology and transceiver parameters of the FDA-MIMO radar system according to claim 2, characterized in that: In step 1.1, Step 1.1.1, perform two launch and three retract configuration; Step 1.1.2, perform four launch and four retract configuration.

4. The method for optimizing spatial topology and transceiver parameters of the FDA-MIMO radar system according to claim 3, characterized in that: In the two-transmit and three-receive configuration, three radars are used in the distributed FDA-MIMO system. When the number of transmitting radars is P (P=2), the number of receiving radars is Q (Q=3), corresponding to I radar nodes (I=3), the transmitting radars and receiving radars of the two radars are co-located FDA-MIMO radars with self-transmitting and self-receiving, and the number of transmitting and receiving array elements are M and N respectively. The remaining third radar is a phased array radar with only passive reception.

5. The method for optimizing spatial topology and transceiver parameters of the FDA-MIMO radar system according to claim 4, characterized in that: In the four-transmit and four-receive configuration, four radars are used in the distributed FDA-MIMO system. When the number of transmitting radars is P (P=4), the number of receiving radars is Q (Q=4), corresponding to I radar nodes (I=4), the transmitting radars and receiving radars of the four radars are co-located FDA-MIMO radars with self-transmitting and self-receiving, and the number of transmitting and receiving array elements are M and N respectively.

6. The method for optimizing spatial topology and transceiver parameters of the FDA-MIMO radar system according to claim 5, characterized in that: In step 1.2, Step 1.2.1, assume that there is a point target in the far field of space located at the origin of the coordinate system. The spatial coordinates of the target relative to the i-th (i=1,2,…,I) radar site are (θ i ,R i ), where θ i represents the angle between the target and the i-th radar station, R i represents the distance between the target and the i-th radar site; Assume that the first array element of the array is the reference coordinate of the corresponding station, and the distance between the array elements is d, and a very small frequency step Δf is introduced between the transmitting radar array elements, and the frequency step is much smaller than the carrier frequency; The signal transmitted by the pth radar (p=1,2,…,P,P≤I) is received by the qth radar (q=1,2,…,Q,Q≤I). The signal-to-interference-to-noise ratio obtained after matched filtering signal processing is SINR pq ; In formula (1), is the expected signal power, is the noise variance; w pq is the receiving weight vector of the qth (q=1,2,…,Q) radar when the pth (p=1,2,…,P) radar transmits; u A is the actual virtual guidance vector of the target; Σ pq (Δf) is the covariance matrix of the clutter between the p-th (p=1,2,…,P) radar and the q-th (q=1,2,…,Q) radar; represents the transpose operation, ||·|| 2 represents the square of the norm; Step 1.2.2: In the two-transmit and three-receive radar configuration of step 1.1.1, the transmitting radar P1 transmits the signal, and the signal-to-interference-to-noise ratio of the receiving radar Q2 receiving the signal output is SINR 12 ; The signal is transmitted by the transmitting radar P2, and the signal to interference noise ratio of the receiving radar Q1 is SINR 21 Therefore, in the two-transmit and three-receive radar configuration, the system's overall output signal-to-interference-to-noise ratio should be subtracted from the SINR 12 and SINR 21 : Step 1.2.3, in the radar configuration of four transmitters and four receivers in step 1.1.2, P = Q = I, and the overall output signal-to-interference-to-noise ratio of the system is:

7. The method for optimizing spatial topology and transceiver parameters of the FDA-MIMO radar system according to claim 6, characterized in that: In step 1.2.1, Step 1.2.1.1, calculate the actual virtual guidance vector u of the target in formula (1) A for; In formula (2), b(θ q ) is the receiving steering vector of the qth (q=1,2,…,Q) radar, a(θ p ,R p ,R q ) is the transmission steering vector of the pth (p=1,2,…,P) radar; Calculate the receiving steering vector b(θ) of the qth radar (q=1,2,…,Q) in formula (2) q ); In formula (3), λ0 is the reference array element wavelength, and H is the conjugate matrix; Calculate the launch steering vector a(θ) of the pth (p = 1, 2, ..., P) radar in formula (2) p ,R p ,R q ); In formula (4), a R (R p ,R q ) is the guidance vector of distance R, a θ (θ p ) is the steering vector of angle θ, ⊙ represents the Hadamard product, and the steering vector of distance R and the steering vector of angle θ in formula (4) are calculated; Step 1.2.2.2, calculate the covariance matrix Σ of the clutter between the pth (p = 1, 2, ..., P) radar and the qth (q = 1, 2, ..., Q) radar in formula (1) pq (Δf); in, represents the clutter noise variance between the pth radar and the qth radar; Indicates at a specific angle Latency The channel response matrix under the sum frequency offset Δf; Radar system output formula (1) Signal-to-noise ratio is accumulated to SINR o ; 8. The method for optimizing spatial topology and transceiver parameters of the FDA-MIMO radar system according to claim 7, characterized in that: In step 2, Step 2.1: In order to maximize the output signal-to-interference-noise ratio, a distributed FDA-MIMO radar system optimization model is constructed. The optimization problem is: In formula (11), Ω i is the set of feasible locations of the i-th (i=1,2,…,I) radar, and the feasible deployment area is modeled as a convex set; Step 2.2, the integer programming problem of formula (11), which is a multi-dimensional NP-hard problem, is solved by a multi-start greedy search algorithm to select the optimal radar site location. The search starts from multiple initial points. During each search process, the site that can minimize the objective function is selected as an alternative solution under the condition that the constraints are met, until the number of sites meets the requirements.

9. The method for optimizing spatial topology and transceiver parameters of the FDA-MIMO radar system according to claim 8, characterized in that: Step 2.2 is as follows: Step 2.2.1, variable initialization, for Let r sn =1; Step 2.2.2, traverse the transmitting array elements and select the transmitting array element that minimizes the objective function; Step 2.2.3, repeat step 2.2.2 until the number of transmitting array elements selected is until; Step 2.2.4, fix the transmitting array element, traverse the receiving array elements, and select the receiving array element that minimizes the objective function; Step 2.2.5, repeat step 2.2.5 until the number of transmitting array elements selected is until.

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