CN113656913B - Distributed forward-looking radar geometric configuration optimization design method - Google Patents
Distributed forward-looking radar geometric configuration optimization design method Download PDFInfo
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Abstract
The invention discloses a geometric configuration optimization design method of a distributed forward-looking radar, which is applied to the technical field of radar detection and imaging and aims at solving the problem of spatial geometric configuration of short-time high-resolution imaging of the distributed forward-looking radar in the prior art; firstly, deriving spatial spectrum distribution by using a spatial geometric configuration of a distributed forward-looking radar, and deriving a quantitative relation between a spatial spectrum and a target point diffusion function; secondly, converting the geometric configuration optimization design problem of the distributed forward-looking radar into a multi-objective constraint problem by constraining factors such as the space spectrum area, the space spectrum shape, the space spectrum acquisition efficiency and the space spectrum filling proportion of the distributed forward-looking radar; and finally, solving the multi-target constraint problem with constraint by adopting a genetic algorithm, and screening the designed space geometric configuration according to parameters such as-3 dB space area of a target point spread function, peak side lobe ratio and integral side lobe ratio of a maximum and minimum resolution direction profile and the like in the solved optimal solution to obtain the optimal geometric configuration of the distributed forward-looking radar.
Description
Technical Field
The invention belongs to the technical field of radar detection and imaging, and particularly relates to a distributed forward-looking radar imaging technology.
Background
The distributed forward-looking radar has a flexible working mode, can provide forward-looking imaging capability for a radar receiver, and has wide application in the fields of military and civil use. However, in a limited observation time, it is difficult to obtain a high-quality fused image because the distributed forward-looking radar coherent imaging system is limited by the geometry between the transmitter and the receiver.
Aiming at the difficult problem of designing the optimal geometric configuration of the distributed forward-looking radar, the literature "Fieder, G.Krieger, F.Jochim, M.Kirschner, and A.Moreira.analysis of biostatic regulations for space SAR interaction [ J ]. Proceedings EUSAR 2002, pp.29-32,2002" proposes the geometric configuration of an interference wheel, and clutter suppression is realized by coherently fusing a plurality of measured values, but the method cannot obtain an optimal imaging result. In documents "f.liu, x.fan, l.zhang, t.zhang, and q.liu.gnss-based SAR for nanoban area imaging: topology optimization and experimental knowledge [ J ]. International Journal of Remote Sensing, vol.40, no.12, pp.4668-4682,2019", a geometric configuration method based on non-coherent fusion point diffusion function evaluation is proposed, which can obtain the optimized geometric configuration of a non-coherent distributed radar, but cannot directly extend the method to a coherent distributed forward-looking radar imaging system because the point diffusion function of the coherent distributed forward-looking radar will exhibit a split main lobe phenomenon under unsuitable configuration conditions.
Disclosure of Invention
In order to solve the technical problems, the invention provides a distributed foresight radar geometric configuration optimization design method, which converts the distributed foresight radar spatial geometric configuration optimization design problem into a multi-objective constraint optimization problem by utilizing the quantitative relation between the spatial spectrum and the point spread function of the distributed radar, obtains the distributed foresight radar optimal geometric configuration by solving the multi-objective constraint optimization problem, and provides an optimized geometric configuration for short-time high-resolution imaging of the distributed foresight radar.
The technical scheme adopted by the invention is as follows: a distributed foresight radar geometric configuration optimization design method comprises the following steps:
s1, defining a forward-looking geometric configuration vector of a distributed radar system according to a sight line included angle between a transmitter and a main receiver, a receiver formation interval and synthetic aperture time;
s2, defining a multi-constraint optimization function of the spatial geometric configuration of the distributed forward-looking radar in a wave number domain according to the forward-looking geometric configuration vector of the distributed radar system in the step S1;
s3, converting the distributed forward-looking radar space geometric configuration multi-constraint optimization function in the step S2 into a multi-objective constraint optimization problem;
s4, solving the multi-target constraint optimization problem in the step S3 to obtain the optimal geometric configuration of the distributed forward-looking radar, namely obtaining the optimal sight line included angle between the transmitter and the main receiver, the optimal receiver formation distance and the optimal synthetic aperture time;
and S5, obtaining a distributed forward-looking radar point spread function according to the optimal geometric configuration obtained in the step S4.
The forward-looking geometric configuration vector expression of the distributed radar system in the step S1 is as follows:
wherein, the first and the second end of the pipe are connected with each other,
a spatial position vector representing the distributed radar system for describing a relative spatial relationship between the transmitter and the receiver; delta theta denotes the line-of-sight angle between the transmitter and the primary receiver, (. DELTA.x,. DELTA.z) denotes the receiver formation distance, T a The synthetic aperture time is indicated.
The distributed forward-looking radar space geometric configuration multi-constraint optimization function expression in the step S2 is as follows:
wherein the content of the first and second substances,
represents the spatial resolution magnitude, <' > or>
Represents a resolution equalization degree>
Represents the difference between the angle of range-azimuth resolution and the orthogonal angle>
Representing the angle between the distance resolution and the lateral distance resolution,
represents the area of the overlap between the (N-1) th spatial spectrum and the first spatial spectrum N, and/or the value of the intensity of the radiation in the radiation beam>
Denotes the minimum overlap region, Ω, of the spatial spectrum 2 Represents a spatial geometry vector +>
The search space of (2).
And S3, converting the distributed forward-looking radar space geometric configuration multi-constraint optimization function into a multi-objective constraint problem by constraining the space spectrum area, the space spectrum shape, the space spectrum acquisition efficiency and the filling proportion of the space spectrum of the distributed forward-looking radar.
The spatial spectrum area of the constrained distributed forward-looking radar is specifically converted into the size of spatial resolution
The constraint distributed forward-looking radar space spectrum shape is characterized in that the resolution balance degree is quantitatively expressed as
The efficiency of obtaining the space spectrum of the constrained distributed forward-looking radar is specifically to convert the minimum overlapping area size of the space spectrum into an echo collection efficiency coefficient
The filling proportion of the space spectrum of the constrained distributed forward-looking radar is specifically that the difference value of a distance and azimuth resolution included angle and an orthogonal angle is converted into a space spectrum filling coefficient.
S3, the expression of the multi-objective constraint optimization problem is as follows:
the step S4 specifically comprises the following steps: and (4) solving the multi-target constraint optimization problem obtained in the step (S3) by adopting a genetic algorithm, and screening the designed space geometric configuration according to the-3 dB space area of the target point spread function, the peak side lobe ratio and the integral side lobe ratio of the maximum and minimum resolution direction profile in the solved multiple optimized solutions to obtain the optimal geometric configuration of the distributed forward-looking radar.
The invention has the beneficial effects that: according to the method, a coherent space spectrum of the distributed forward-looking radar is constrained in a space spectrum domain, a geometric configuration optimization problem of the distributed forward-looking radar is converted into a multi-constraint optimization problem, a focused, balanced and regular point target function can be obtained through solving the multi-constraint optimization problem, and a foundation is laid for coherent fusion of data of a plurality of receivers of the distributed forward-looking radar in limited observation time and obtaining of a high-resolution radar image;
according to the method, the space geometric design problem of the distributed forward-looking radar is converted into a multi-objective constraint optimization problem, and the space geometric configuration optimization design of the distributed forward-looking radar for short-time high-resolution imaging is achieved.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a diagram of a distributed forward-looking radar geometry model provided by an embodiment of the present invention;
FIG. 3 is a comparison of a point spread function for a distributed forward-looking radar geometry optimization feasible solution provided by an embodiment of the invention;
wherein, FIG. 3 (a) is the spatial spectrum support region distribution of feasible solution of geometry 1; FIG. 3 (b) is the spatial spectrum support region distribution of a feasible solution for geometry 2; FIG. 3 (c) is a spatial spectral support region distribution of a feasible solution for geometry 3; FIG. 3 (d) is the point spread function imaging result of the primary receiver in the designed spatial geometry of geometry 1; FIG. 3 (e) is a diagram showing the point spread function imaging result of the primary receiver in the spatial geometry designed for geometry 2; FIG. 3 (f) is a diagram showing the point spread function imaging result of the primary receiver in the spatial geometry designed for geometry 3; FIG. 3 (g) shows the results of point spread function imaging from the receiver in the spatial geometry designed for geometry 1; FIG. 3 (h) shows the result of point spread function imaging from the receiver in the spatial geometry designed for geometry 2; FIG. 3 (i) shows the results of point spread function imaging from the receiver in the spatial geometry designed for geometry 3; FIG. 3 (j) is a plot of the point spread function imaging results from the receiver in the spatial geometry designed for geometry 1; FIG. 3 (k) is a diagram of the imaging result of the point spread function of the receiver in the spatial geometry designed for geometry 2, and FIG. 3 (l) is a diagram of the imaging result of the point spread function of the receiver in the spatial geometry designed for geometry 3;
fig. 4 is a comparison of the imaging results of the geometry optimization of the one-transmit-two-receive distributed forward-looking radar provided by the embodiment of the present invention;
fig. 4 (a) shows the imaging result of the master receiver, fig. 4 (b) shows the imaging result of the slave receiver, and fig. 4 (c) shows the imaging result after coherent fusion.
Detailed Description
The effectiveness of the proposed distributed forward-looking radar geometric configuration optimization design method is verified mainly by adopting a simulation experiment method. All steps and conclusions are verified to be correct on the Windows10 operating system through the MATLAB 2018a platform. To facilitate understanding of the technical disclosure of the present invention, the following description is provided in conjunction with the accompanying drawings.
The flow chart of the method of the invention is shown in figure 1.
The method comprises the following steps: echo model and spatial spectrum coherent projection of distributed forward-looking radar
For convenience of description, the distributed forward-looking radar system of the present invention is comprised of a transmitter and N receivers, the geometry of which is shown in fig. 2. The radar system parameters are shown in table 1.
TABLE 1 distributed Forward-view Radar System parameter Table
The transmitter being spatially located at
R T Representing the distance between the transmitter and the target O, the target O having coordinates (0,0,0), θ T Is azimuth angle->
Is the pitch angle, the subscript T is used to identify the Transmitter related parameters, and the full spelling of T is transmit. The Nth receiver is located->
Rectangular coordinate of
Receiver based on speed->
Flying to target O, wherein>
And v represent the direction and magnitude of the velocity, respectively. The maximum distribution spacing of the receivers is (Δ x,0,. DELTA.z) wherein the first receiver is the master receiver and the first receiver is located in->
The second through N-1 receiver coordinates are evenly distributed between the first and nth. The target P is located on the ground plane with coordinates (x, y, 0). The distances from the Nth receiver and transmitter to the target point P are R RNP And R TP 。
The transmitter transmits a Linear Frequency Modulated (LFM) signal and the received signal reflected from the target P for the Nth receiver may be represented as
Wherein, A represents the echo amplitude and is related to the scattering coefficient of the target, the power of the transmitted signal and the like; tau, T, T a And T r Respectively representing slow sampling time, fast sampling time, synthetic aperture time and signal time width; c represents the propagation velocity of the electromagnetic wave. f. of c And K r Respectively, the carrier frequency and chirp rate. The distance history of the target P may be represented as R NP (τ)＝R TP (τ)+R RNP (τ). It will be noted by those skilled in the art that R TP (τ) is the change in distance with slow time, R TP ＝R TP (0) Is the distance of the starting instant.
The echo data can be converted into a range frequency domain by using the principle of stationary phase
Wherein f is t Representing the range frequency. The echo data of the point P may be represented as
Wherein R is NO (τ)＝R T (τ)+R N (τ) represents the historical distance of the reference target. The difference in historical distance between target P and target O is:
the transmitter and each receiver may form a set of spatial dual-basis forward-looking radar systems. For the Nth bistatic radar pair, the spatial spectral variables in the x and y directions can be defined as
Thus, the nth bistatic radar log domain echo data can be expressed as:
s N (k xN ,k yN )＝A·exp[j(xk xN +yk yN )] (6)
coordinate (k) in the wavenumber domain as shown in equation (5) xN ,k yN ) Varying with the transmission frequency and the spatial location of the transceiving stations. The extent of the spatial spectrum support region can be expressed as:
wherein k is xN (τ,f t ) And k yN (τ,f t ) Vectors representing the spatial spectral variables in the x and y directions of the nth pair of bistatic radar pairs, respectively. [ k ] A xminN ,k xmaxN ]And [ k ] yminN ,k ymaxN ]The boundaries of the analysis range of the spatial spectrum supporting region in the Nth bistatic radar pair along the x direction and the y direction are respectively defined.
The position of the spatial spectrum distribution region is determined by the relative spatial sampling relation, and the range boundaries of a plurality of double-base pair spatial spectrum distribution regions of the distributed forward-looking radar system along the directions of x and y are
Wherein min {. Cndot } and max {. Cndot } represent minimum and maximum operations, respectively.
According to the position relation among a plurality of stations, echo data of the distributed forward-looking radar system are coherently projected to a spatial spectrum domain
Wherein, A n ' denotes the normalized amplitude, s, of the fused spatial spectrum n (k xn ,k yn ) Representing the nth bistatic radar log domain echo data.
Step two: geometry estimator design for distributed radar
According to the fusion spatial spectrum data derived in the first step, for a single-point scattering target, a point spread function of the system can be obtained through two-dimensional fast Fourier transform and can be expressed as
Wherein PSF (x, y) represents the scattering coefficient of the target at the (x, y) location, and Ω represents the effective range defined by the boundaries of the spatial spectral distribution region of the distributed radar system. By using the transformation relation of equation (17), the target spatial resolution characteristic can be directly evaluated in the spatial spectral domain.
In the invention, the included angle of the sight line between the main transmitter and the main receiver is Delta theta =θ 1 -θ T Receiver formation spacing (Δ x, Δ z) and synthetic aperture time T a And (5) carrying out optimized design. Thus, a forward-looking geometry vector for a distributed radar system may be defined
Is composed of
Wherein the content of the first and second substances,
represents a spatial position vector of the distributed radar system that describes the relative spatial relationship between the transmitter and the receiver. Therefore, the distributed forward-looking radar space geometry multi-constraint optimization function can be defined as ^ greater than or equal to in the wave number domain>
Wherein the optimization functions (a) and (b) in equation (12) respectively represent minimizing the spatial resolution size
And resolution equalization degree>
The optimization function (c) in equation (12) constrains the angle between the range resolution and the lateral range resolution from the spatial spectral domain>
Representing the difference between the distance and azimuth resolution included angle and the orthogonal angle; the optimization function (d) in equation (12) represents minimizing the overlapping area of adjacent spatial spectra, according to which the value of the function (d) is selected>
Represents the (N-1) thThe overlapping area between the spatial spectrum and the Nth spatial spectrum; />
The minimum overlap region that constrains the spatial spectrum should be greater than 0, Ω 2 Indicating a spatial geometry vector in attached Table 1>
Search space of (i.e., in Table 1 +)>
Search space containing four parameters).
In order to quantitatively evaluate the performance of the spatial resolution of the distributed forward-looking radar from the spatial spectral domain, the optimization function of the spatial resolution size in the optimization function (a) in equation (12) can be converted into
Wherein S is w Representing the area size of the spatial spectrum supporting region;
representing a spatial vector being &>
The area of the spatial spectrum support region is small.
In order to constrain the resolution equalization degree of the point spread function of the distributed forward-looking radar, the resolution equalization coefficient in the optimization function (b) in equation (12) can be quantitatively expressed as
Wherein the content of the first and second substances,
and &>
Respectively representing the spatial spectrum in the direction of maximum resolution phi max And a minimum resolution direction phi min The projected bandwidth of (c).
To constrain the shape of the point spread function of the distributed forward-looking radar, the resolution spatial angle in the optimization function (c) in equation (12) can be converted to a spatial spectral fill factor of
Wherein S is r And the area size of a circumscribed rectangle of the spatial spectrum supporting region is represented.
In order to constrain the synthetic aperture time of the distributed radar and improve the data acquisition efficiency, the minimum spatial spectrum overlap region in the optimization function (d) in the formula (12) can be converted into an echo acquisition efficiency coefficient
Wherein the content of the first and second substances,
indicates that the space vector is->
The area of the (N-1) th spatial spectrum supporting region is measured; />
Indicates that the space vector is->
And (3) the area of the Nth spatial spectrum supporting region. S rmin ＝min{S r (φ 1 ),…,S r (φ i ),…,S r (φ I ) Denotes the minimum area of the bounding rectangle, phi i Representing the spatial projection direction of the spatial spectrum.
Therefore, the optimization problem of the spatial geometry optimization design constraint of the distributed forward-looking radar in the formula (12) can be converted into
By converting equation (12) into the multi-constraint optimization problem in equation (17), the spatial resolution performance of the distributed forward-looking radar can be quantitatively described in the spatial spectrum domain.
Step three: distributed foresight radar geometric configuration optimization solution
The invention adopts a genetic algorithm of nonlinear constraint non-dominated sorting to solve a multi-constraint optimization problem (17) so as to obtain the space geometric configuration parameters of the distributed forward-looking radar.
A. Firstly, initializing geometric configuration optimization design: the geometry optimization design initialization consists of two parts. In one aspect, parameters of a distributed radar system are set. On the other hand, multi-constraint optimization solving algorithm initialization, such as maximum algebra G max Population size K P Optimal solution ratio P γ Cross ratio P c And the variation ratio P m . The initial population of geometry vectors is
Randomly generated from the decision space. Wherein, the maximum algebra G max =200, population size K P =30, optimal solution ratio P γ =0.1, cross ratio P c =0.8 and variation ratio P m ＝0.2。
B. Second, crossover and mutation operations: for generation G, population I G For generating offspring populations O by means of crossover operators and mutation operators G . Generated progeny population O G And the parent group I G Are combined to obtain a population P G ＝O G ∪I G 。
C. Next, non-dominated sorting, based on the constraints in (17), a solution may be feasibleMay also be infeasible. The concept of constraint dominance is introduced in non-dominated sorting. If any of the following conditions is true, the solution P is called i G Constraint dominated solution P j G (P i G ＜ c P j G ) (ii) a a) Solution of P i G Feasible, solution P j G Is not feasible; b) Solution of P i G And P j G None are feasible, but solution P i G The constraint value of (2) is smaller; c) Solution of P i G And P j G All are feasible, but solve P i G Constraint dominated solution P j G . With this constrained control principle, any feasible solution may have a better non-controlled rank than any infeasible solution. All feasible solutions are sorted according to their objective function values and constraint values. Solutions with the same non-dominant level are assigned to the same non-dominant front.
D. Further, contest selection: the congestion distance of each non-dominant leading edge solution is calculated to evaluate the congestion degree of each non-dominant leading edge solution. Bituming selection based on congestion comparison operator and rank is used to select the generated population U G+1 . Then generating a group U G+1 Allocation for crossover and mutation to create a new parent group I G+1 . Contest scale of T = P γ *K P 。
E. Subsequently, the screening of the optimized geometries: based on the evolutionary updating process in the steps B to D, when the iterative algebra is more than G max Multiple feasible solutions for the geometry vector may be obtained. However, the solved point spread function may exhibit different characteristics. In order to evaluate the performance of the designed spatial geometry, a feasible solution of the design is screened by comparing peak sidelobe ratios and integral sidelobe ratios of the key diffusion function in different directions. Example G max The value is 200.
The system parameters and the constraint optimization algorithm initialization parameters according to the invention, and the spatial geometrical configurations of the three sets of designs are shown in table 2. In table 2, geometry 1 achieved better equalization of point spread function with a resolution equalization ratio of 1.96 and geometry 2 achieved better equalizationGood space spectrum filling ratio, more regular point diffusion function of reconstruction, 80.21 percent of space spectrum filling ratio, and 3.63m of higher spatial resolution obtained by geometric configuration 2 。
TABLE 2 optimal design of the spatial geometry solution and its spatial resolution performance parameters
The comparison of the feasible solution point spread function for distributed forward-looking radar geometry optimization is shown in fig. 3. FIGS. 3 (a) - (c) are three possible solution spatial spectrum support region distributions; FIGS. 3 (d) - (f) are the results of point spread function imaging of the primary receiver in three sets of spatial geometries designed; FIGS. 3 (g) - (i) are the results of point spread function imaging from the receiver in three sets of spatial geometries designed; fig. 3 (j) - (l) show the results of point spread function imaging from the receiver in three sets of spatial geometries designed. From the results, the coherent-fused point spread function can effectively improve the spatial resolution of the distributed forward-looking radar within the limited synthetic aperture time.
Second, the point spread function for the three sets of designed spatial geometries is along the direction of maximum resolution φ max And a minimum resolution direction phi min The Peak-to-side lobe ratio (PSLR) and the Integrated Side Lobe Ratio (ISLR) of (iii) were compared, and the results are shown in table 3, and it can be seen from table 3 that configuration 3 can obtain more excellent imaging performance.
TABLE 3 Peak to integral sidelobe ratio of Point spread function after fusion
Step four: distributed forward-looking radar coherent fusion imaging
Based on the spatial geometric configuration and radar system parameters of the distributed forward-looking radar screened in the third step, the target scattering coefficient of the surface target scene is reintroduced, the first step is repeated, short-time high-resolution imaging of the distributed forward-looking radar is achieved through two-dimensional fast Fourier transform, and the imaging result can be expressed as
Where σ (x, y) represents the scattering coefficient of the target at the (x, y) position, and Ω represents the effective range defined by the boundaries of the spatial spectral distribution region of the distributed radar system.
In the one-shot two-receiver distributed forward-looking radar system, according to the optimized geometric configuration 3, the receiver and the fusion imaging result are shown in fig. 4. Fig. 4 (a) is the imaging result of the master receiver, fig. 4 (b) is the imaging result of the slave receiver, fig. 4 (c) is the imaging result after coherent fusion, and it can be found in fig. 4 (c) that in the same synthesis space time, the method of the present invention can obtain the imaging result with higher resolution by the fusion of the geometry optimization and the coherent data.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (6)
1. A distributed foresight radar geometric configuration optimization design method is characterized by comprising the following steps:
s1, defining a forward-looking geometric configuration vector of a distributed radar system according to a sight line included angle between a transmitter and a main receiver, a receiver formation interval and synthetic aperture time; the forward-looking geometric configuration vector expression of the distributed radar system in the step S1 is as follows:
wherein, the first and the second end of the pipe are connected with each other,
a spatial position vector representing the distributed radar system for describing a relative spatial relationship between the transmitter and the receiver; delta theta denotes the line-of-sight angle between the transmitter and the primary receiver, (. DELTA.x,. DELTA.z) denotes the receiver formation distance, T a Represents the synthetic aperture time;
s2, defining a multi-constraint optimization function of the spatial geometric configuration of the distributed forward-looking radar in a wave number domain according to the forward-looking geometric configuration vector of the distributed radar system in the step S1; the distributed forward-looking radar space geometric configuration multi-constraint optimization function expression in the step S2 is as follows:
wherein the content of the first and second substances,
represents the spatial resolution magnitude, <' > or>
Represents a resolution equalization degree>
Represents the difference between the angle of range-azimuth resolution and the orthogonal angle>
Representing the angle between the distance resolution and the lateral distance resolution,
represents the area of the overlap between the (N-1) th spatial spectrum and the first spatial spectrum N, and/or the value of the intensity of the radiation in the radiation beam>
Denotes the minimum overlap region, Ω, of the spatial spectrum 2 Represents a spatial geometry vector pick>
The search space of (2);
s3, converting the distributed forward-looking radar space geometric configuration multi-constraint optimization function in the step S2 into a multi-objective constraint optimization problem; s3, converting a distributed forward-looking radar space geometric configuration multi-constraint optimization function into a multi-objective constraint problem by constraining the space spectrum area, the space spectrum shape, the space spectrum acquisition efficiency and the filling proportion of the space spectrum of the distributed forward-looking radar; s3, the expression of the multi-objective constraint optimization problem is as follows:
s4, solving the multi-target constraint optimization problem in the step S3 to obtain the optimal geometric configuration of the distributed forward-looking radar, namely obtaining the optimal sight angle between the transmitter and the main receiver, the optimal formation distance of the receivers and the optimal synthetic aperture time;
and S5, obtaining a distributed forward-looking radar point spread function according to the optimal geometric configuration obtained in the step S4.
2. The method as claimed in claim 1, wherein the constraint distributed forward-looking radar space is designed based on the geometric configuration optimizationInter-spectral area, in particular to convert the size of spatial resolution into
Indicates that the space vector is->
The area of the spatial spectrum supporting region is small.
3. The method as claimed in claim 2, wherein the spatial spectrum shape of the distributed forward-looking radar is constrained, specifically, resolution balance is quantitatively expressed as
Wherein the content of the first and second substances,
and &>
Respectively representing the spatial spectrum in the direction of maximum resolution phi max And a minimum resolution direction phi min The projected bandwidth of (c).
4. The method as claimed in claim 3, wherein the acquisition efficiency of the spatial spectrum of the distributed forward-looking radar is constrained, specifically, the minimum overlapping area size of the spatial spectrum is converted into an echo collection efficiency coefficient
Wherein the content of the first and second substances,
representing a spatial vector being &>
The area of the (N-1) th spatial spectrum supporting region is measured; />
Indicates that the space vector is->
The area of the Nth spatial spectrum supporting region is larger than that of the Nth spatial spectrum supporting region; s rmin Representing the minimum area of the circumscribed rectangle.
5. The method as claimed in claim 4, wherein the filling ratio of the spatial spectrum of the distributed forward-looking radar is constrained, specifically, a difference between a range-azimuth resolution included angle and an orthogonal angle is converted into a spatial spectrum filling coefficient.
6. The method for optimally designing the geometric configuration of the distributed forward-looking radar according to claim 5, wherein the step S4 is specifically as follows: and (3) solving the multi-target constraint optimization problem obtained in the step (S3) by adopting a genetic algorithm, and screening the designed space geometric configuration according to the-3 dB space area of the target point spread function, the peak side lobe ratio and the integral side lobe ratio of the maximum and minimum resolution direction profile in the solved multiple optimization solutions to obtain the optimal geometric configuration of the distributed forward-looking radar.
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