Clutter suppression capability rapid evaluation method based on space-based double-station detection system

Abstract

The invention discloses a clutter suppression capability rapid evaluation method based on a space-based double-station detection system, and solves the problems of large calculation amount and low calculation speed when output signal-clutter-noise ratio loss is used for evaluating the space-based double-station clutter suppression capability in an actual calculation process in the prior art. The method comprises the following steps: acquiring a target airspace steering vector, and calculating a fuzzy clutter airspace steering vector of each fuzzy distance ring according to a fuzzy condition; calculating an included angle corresponding to each fuzzy distance ring, and calculating a mean value according to the included angle corresponding to each fuzzy distance ring; the deviation degree between the two is calculated according to the included angle and the mean value; constructing an unambiguous airspace clutter covariance matrix in an ideal state, and obtaining an ideal signal-clutter-noise ratio; taking the target airspace steering vector as a weight vector to obtain an actual signal-clutter-noise ratio, and obtaining target output signal-clutter-noise ratio loss according to the ideal signal-clutter-noise ratio and the actual signal-clutter-noise ratio; according to the method, the clutter suppression capability is rapidly evaluated under a space-based double-station detection system.

Description

Technical Field

[0001] The present invention relates to the technical field of radar, and particularly relates to a method for rapidly evaluating the clutter suppression ability under a space-based bistatic detection system. Background Art

[0002] A space-based bistatic radar has no satellite source. Through the design of joint observation with the transmitting satellite, the transmitting satellite is not easily attacked and the receiving satellite is not easily detected. It has advantages such as anti-stealth, anti-radiation missile, anti-comprehensive electronic interference, and anti-low-altitude penetration, and has an important position in practical applications. However, when the radar is in a downward-looking detection state, strong ground clutter will submerge the target, and clutter suppression faces key technical challenges. Space-Time Adaptive Processing (STAP) constructs a space-time joint filter and uses the space-Doppler characteristics of clutter to optimize the weights, so as to suppress clutter interference to the greatest extent while enhancing the target signal. The clutter suppression ability is used to measure the performance of STAP. First, the theoretical covariance matrix is calculated according to the spatial steering vector of the scattering unit competing with the target distance and Doppler frequency on the ambiguity distance ring, and then the weight vector is calculated to obtain the output signal-to-clutter-plus-noise ratio (SCNR). Finally, the output SCNR loss is calculated to evaluate the clutter suppression ability. However, the calculation amount designed to calculate the SCNR loss by this method to evaluate the clutter suppression ability is large, resulting in the inability to quickly obtain the clutter suppression ability.

[0003] At the same time, the array distribution will also affect the STAP processing. When the array is a broadside array, the clutter spectrum is diagonally distributed in the space-time two-dimensional plane and does not change with distance, that is, the clutter spectra at each range cell coincide, and there is no clutter spectrum broadening phenomenon. Therefore, the data of adjacent range cells can be used as training samples to estimate the clutter correlation matrix. However, when the array is a non-broadside array, the clutter power spectrum is no longer linearly distributed in the space-time two-dimensional plane, but elliptically distributed, and the ellipse size changes with distance, that is, the clutter spectra at different distances do not coincide, which is called the range dependence of clutter. At this time, if the data of adjacent range cells are still directly used to estimate the clutter correlation matrix, the resulting adaptive weights will form a wide and shallow notch at the clutter of the cell to be detected, which not only cannot effectively suppress clutter, but may also filter out weak and slow target signals, resulting in a large range of target detection blind areas. The existing processing method is to reduce the range dependence of clutter by compensating the clutter spectrum, so as to obtain enough uniform samples, which will further increase the calculation amount.

[0004] At present, a classical method for evaluating the clutter suppression ability of space-based radar has been obtained based on the principle of space-time adaptive processing. By calculating the space-time vector of the target, the weight vector of the echo signal, and the clutter covariance matrix in the presence of noise, and then calculating the output signal-to-clutter-plus-noise ratio (SCNR) of the optimal STAP processor, the clutter suppression performance is finally obtained through the SCNR loss. In addition, various reduced-dimension STAP algorithms such as local joint processing and three-dimensional Doppler-space-time adaptive processing have been proposed. By performing narrowband Doppler filtering in the time domain, the degrees of freedom of clutter are greatly reduced, so that fewer time-domain degrees of freedom can be used to participate in space-time joint processing, which can reduce the computational complexity.

[0005] At present, the existing method is as follows: determining the multi-channel space-time two-dimensional received signal model according to the radar system parameters; based on the multi-channel space-time two-dimensional received signal model, determining the discrete clutter data vector model of only the spatial domain dimension of the current unit to be detected under post-Doppler processing, which includes the perturbation components introduced by non-ideal orthogonal waveforms; based on the multi-channel data vector model for determining the non-ideal factors of the current unit to be detected; based on determining the clutter covariance matrix including non-ideal factors; according to the expression for determining the STAP clutter suppression weight vector; according to the expression of the clutter covariance matrix and the STAP clutter suppression weight vector and the output SCNR loss model, determining the STAP evaluation model under non-ideal factors.

[0006] The existing clutter suppression evaluation method calculates the theoretical covariance matrix according to the spatial steering vector of the scattering cells competing with the target distance and Doppler frequency on the ambiguous distance ring, and then calculates the weight vector to obtain the output signal-to-clutter-plus-noise ratio SCNR, and finally calculates the output signal-to-clutter-plus-noise ratio loss to evaluate the clutter suppression ability. The limitation of this method is that the complexity of calculating the clutter covariance matrix is high, and at the same time, the covariance matrix needs to be inverted when calculating the weight vector, which leads to high computational complexity, slow operation speed, and inability to obtain results quickly. Summary of the Invention

[0007] The present invention provides a method for quickly evaluating the clutter suppression ability under the space-based bistatic detection system, which solves the problems of large amount of calculation and slow operation speed in the actual calculation process when using the output signal-to-clutter-plus-noise ratio loss to evaluate the space-based bistatic clutter suppression ability in the prior art, and realizes the quick evaluation of the clutter suppression ability under the space-based bistatic detection system.

[0008] In a first aspect, the present invention provides a method for quickly evaluating the clutter suppression ability under the space-based bistatic detection system, the method comprising:

[0009] Obtaining the target spatial steering vector, and calculating the ambiguous clutter spatial steering vectors of each ambiguous distance ring according to the ambiguous situation;

[0010] Calculate the included angle corresponding to each ambiguous range ring according to the ambiguous clutter spatial domain steering vector of each ambiguous range ring and the target spatial domain steering vector, and calculate the mean value according to the included angle corresponding to each ambiguous range ring;

[0011] Calculate the deviation degree between the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector according to the included angle corresponding to each ambiguous range ring and the mean value;

[0012] Construct an unambiguous clutter covariance matrix in the ideal state according to the unambiguous clutter steering vector in the spatial domain, and calculate the ideal signal-to-clutter ratio according to the unambiguous clutter covariance matrix, the deviation degree, and the target spatial domain steering vector;

[0013] Use the target spatial domain steering vector as the weight vector to obtain the actual signal-to-clutter ratio, and obtain the target output signal-to-clutter ratio loss according to the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio.

[0014] In a first aspect, in a possible implementation manner, the calculating the ambiguous clutter spatial domain steering vector of each ambiguous range ring according to the ambiguity situation includes:

[0015] Determine the number of ambiguous range rings, and calculate the slant range R corresponding to each ambiguous range ring sm ;

[0016] According to the slant range R corresponding to each ambiguous range ring sm and the height from the satellite to the sub-satellite point, calculate the detection range R corresponding to each ambiguous range ring m ;

[0017] According to the slant range R corresponding to each ambiguous range ring sm and the detection range R m , calculate the elevation angle θ corresponding to each ambiguous range ring ELm ;

[0018] Divide each ambiguous range ring into multiple clutter scattering units, and calculate the azimuth angle θ corresponding to each clutter scattering unit AZm,i ;

[0019] According to the Doppler frequency of the target, calculate the number i of clutter scattering units competing with the target on each ambiguous range ring and the azimuth angle θ corresponding to each scattering unit AZm,i ;

[0020] According to the elevation angle θ corresponding to each ambiguous range ring ELm and the azimuth angle θ of the i-th clutter scattering unit competing with the target on each ambiguous range ring AZm,i , calculate the spatial domain steering vector s of each scattering unit on each ambiguous range ring m,i .

[0021] Determine the clutter spatial steering vectors of each ambiguous range ring through the spatial steering vectors s of all clutter scattering units competing with the target on each ambiguous range ring m,i Determine the clutter spatial steering vectors of each ambiguous range ring.

[0022] In a first aspect, in a possible implementation manner, according to the slant range R corresponding to each of the ambiguous range rings sm and the height of the satellite to the sub-satellite point, calculate the detection range R corresponding to each ambiguous range ring m , including:

[0023] According to the slant range R corresponding to each of the ambiguous range rings sm and the height of the satellite to the sub-satellite point, use the detection range calculation formula to calculate the detection range R corresponding to each ambiguous range ring m ;

[0024] The detection range calculation formula is expressed as:

[0025]

[0026] wherein, R m represents the detection range corresponding to the m-th ambiguous range ring; R e represents the radius of the earth; H represents the height of the satellite to the sub-satellite point; R sm represents the slant range of the m-th ambiguous range ring; M represents the ambiguity number.

[0027] In a first aspect, in a possible implementation manner, the calculating the included angle corresponding to each ambiguous range ring according to the ambiguous clutter spatial steering vectors of each ambiguous range ring and the target spatial steering vector includes:

[0028] Calculate the included angle corresponding to each ambiguous range ring according to the ambiguous clutter spatial steering vectors of each ambiguous range ring and the target spatial steering vector by using the included angle formula;

[0029] wherein, the included angle formula is expressed as:

[0030]

[0031] wherein, s tar represents the target spatial steering vector; s m represents the ambiguous clutter spatial steering vector on the m-th ambiguous range ring; represents the conjugate transpose vector of the ambiguous clutter spatial steering vector on the m-th ambiguous range ring; ψ m represents the included angle between the m-th ambiguous range ring and the target spatial steering vector; the value range of m.

[0032] In a first aspect, in a possible implementation, calculating the deviation between the fuzzy clutter spatial domain steering vector and the target spatial domain steering vector based on the included angles and means corresponding to each fuzzy distance ring includes:

[0033] Calculating the deviation between the fuzzy clutter spatial domain steering vector and the target spatial domain steering vector according to the included angles and means corresponding to each fuzzy distance ring by using a deviation calculation formula;

[0034] Among them, the deviation calculation formula is expressed as:

[0035]

[0036] Among them, ψ m represents the included angle between the spatial domain steering vector corresponding to all scattering units on the m-th fuzzy distance ring and the target spatial domain steering vector; ψ0 represents the mean value of the included angles between the spatial domain steering vector corresponding to all scattering units on the m-th fuzzy distance ring and the target spatial domain steering vector; m ∈ (0, M); M represents the number of ambiguity times; σ represents the deviation.

[0037] In a first aspect, in a possible implementation, calculating the ideal signal-to-clutter-plus-noise ratio based on the unambiguous spatial clutter covariance matrix, the deviation, and the target spatial domain steering vector includes:

[0038] Solving the inverse matrix of the unambiguous spatial clutter covariance matrix;

[0039] Calculating the optimal weight vector in the ideal state through the product of the inverse matrix, the target spatial domain steering vector, and the deviation;

[0040] Applying the optimal weight vector to the target signal to calculate the ideal signal-to-clutter-plus-noise ratio.

[0041] In a first aspect, in a possible implementation, taking the target spatial domain steering vector as the weight vector to obtain the actual signal-to-clutter-plus-noise ratio, and obtaining the target output signal-to-clutter-plus-noise ratio loss according to the ideal signal-to-clutter-plus-noise ratio and the actual signal-to-clutter-plus-noise ratio includes:

[0042] Taking the target spatial domain steering vector as the weight vector, performing STAP filtering on the fuzzy clutter spatial domain steering vectors of each fuzzy distance ring and calculating the output signal power P;

[0043] Based on the output signal power P, obtaining the actual signal-to-clutter-plus-noise ratio;

[0044] Performing numerical conversion on the ideal signal-to-clutter-plus-noise ratio and the actual signal-to-clutter-plus-noise ratio respectively to obtain the first ideal signal-to-clutter-plus-noise ratio and the first actual signal-to-clutter-plus-noise ratio;

[0045] Calculate the target output signal-to-clutter-noise ratio (SCNR) loss based on the first ideal SCNR and the first actual SCNR.

[0046] In a first aspect, in a possible implementation, the calculation of the target output SCNR loss based on the first ideal SCNR and the first actual SCNR is achieved through the following formula:

[0047] SCNR Loss (dB) = SCNR out (dB) - SNR(dB);

[0048] where SCNR Loss (dB) represents the target output SCNR loss; SNR(dB) represents the first actual SCNR; SCNR out (dB) represents the first ideal SCNR.

[0049] In a second aspect, the present invention provides a device for rapidly evaluating the clutter suppression ability under a space-based bistatic detection system. The device includes:

[0050] An initialization module, configured to obtain the target spatial domain steering vector and calculate the ambiguous clutter spatial domain steering vectors of each ambiguous range ring according to the ambiguity situation;

[0051] An included angle calculation module, configured to calculate the included angles corresponding to each ambiguous range ring according to the ambiguous clutter spatial domain steering vectors of each ambiguous range ring and the target spatial domain steering vector, and calculate the average value according to the included angles corresponding to each ambiguous range ring;

[0052] A deviation calculation module, configured to calculate the deviation between the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector according to the included angles corresponding to each ambiguous range ring and the average value;

[0053] An ideal SCNR calculation module, configured to construct an ideal clutter covariance matrix of the non-ambiguous spatial domain according to the non-ambiguous spatial domain clutter steering vector, and calculate the ideal SCNR according to the non-ambiguous spatial domain clutter covariance matrix, the deviation, and the target spatial domain steering vector;

[0054] An output module, configured to obtain the actual SCNR with the target spatial domain steering vector as the weight vector, and obtain the target output SCNR loss according to the ideal SCNR and the actual SCNR.

[0055] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0056] The present invention obtains the deviation degree between the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector by using the included angle between the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector and its mean value; the present invention constructs an unambiguous clutter spatial domain covariance matrix under ideal conditions according to the unambiguous clutter spatial domain steering vector, and calculates the target output according to the unambiguous clutter spatial domain covariance matrix, the deviation degree and the target spatial domain steering vector; without calculating the covariance matrix of the clutter and its corresponding inverse of the covariance matrix, the present invention directly conducts a rapid evaluation of the clutter suppression ability, significantly reducing the computational amount and improving the speed of evaluating the clutter suppression ability under the space-based bistatic detection system; and under the space-based bistatic detection system, the clutter covariance matrix is related to the clutter spatial domain steering, so the ambiguous interference phase difference can reflect the spatial domain vector difference, and the smaller the ambiguous interference phase difference, the better the system performance; the present invention uses the target theoretical spatial domain steering vector as the weight vector, and when facing the problem of clutter range dependence caused by non-side-looking arrays, it can avoid the problem of being unable to suppress clutter when directly using the cell data to estimate the clutter correlation matrix and filtering out weak and slow target signals, resulting in a large-range target detection blind area. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 FIG. is a flowchart of the steps of a method for rapidly evaluating the clutter suppression ability based on a space-based bistatic detection system provided by an embodiment of the present invention;

[0058] Figure 2 FIG. is a schematic diagram of the angle corresponding to the ambiguous distance in the space-based bistatic mode provided by an embodiment of the present invention;

[0059] Figure 3 FIG. is a comparison chart of the output SCNR loss curves provided by an embodiment of the present invention;

[0060] Figure 4 FIG. is a quantitative comparison result chart of the gap between two evaluation methods provided by an embodiment of the present invention;

[0061] Figure 5 FIG. is a comparison result chart of the computational complexity of two evaluation methods provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0063] The present invention provides a method for rapidly evaluating the clutter suppression ability based on a space-based bistatic detection system. Refer to Figure 1, the method includes the following steps S104 to S104.

[0064] S101. Obtain the target airspace steering vector, and calculate the ambiguous clutter airspace steering vectors of each ambiguous range ring according to the ambiguity situation;

[0065] Specifically, the target airspace steering vector is expressed as:

[0066]

[0067] where, θ EL represents the elevation angle of the target; θ AZ represents the azimuth angle of the target; d represents the distance between adjacent array elements; λ represents the signal wavelength; N represents; s tar represents the target airspace steering vector.

[0068] Specifically, in step S101, calculating the ambiguous clutter airspace steering vectors of each ambiguous range ring according to the ambiguity situation includes the following S1011 to S1016.

[0069] S1011. Determine the number of ambiguous range rings, M represents the ambiguity times, and calculate the slant range R sm .

[0070] Here, the slant range R sm is expressed as:

[0071] R sm =R S +m×δ SR (1.2)

[0072] where, R sm represents the slant range of the mth ambiguous range ring; R S represents the slant range of the range ring where the target is located, R e represents the radius of the earth, H represents the height of the satellite from the sub-satellite point, R H represents the distance from the sub-satellite point to the target; m represents the mth ambiguous range ring; δ SR represents the radar resolution in the slant range.

[0073] S1012. According to the slant range R sm corresponding to each ambiguous range ring and the height of the satellite from the sub-satellite point, calculate the detection range R m corresponding to each ambiguous range ring by using the detection range calculation formula.

[0074] Here, the detection range calculation formula is expressed as:

[0075]

[0076] Among them, R m represents the detection distance corresponding to the m-th ambiguity range ring; R e represents the radius of the Earth; H represents the height of the satellite from the sub-satellite point; R sm represents the slant range of the m-th ambiguity range ring; M represents the ambiguity times.

[0077] S1013. According to the slant range R sm and the detection distance R m corresponding to each ambiguity range ring, calculate the elevation angle θ ELm corresponding to each ambiguity range ring.

[0078] Here, the elevation angle θ ELm corresponding to each ambiguity range ring is expressed as:

[0079]

[0080] S1014. According to the Doppler frequency of the target, calculate the number i of clutter scattering cells competing with the target on each ambiguity range ring and the azimuth angle θ AZm,i corresponding to each scattering cell.

[0081] Here, the azimuth angle θ AZm,i corresponding to each clutter scattering cell is expressed as:

[0082]

[0083] Among them, v r represents the radial velocity of the target relative to the satellite, V represents the motion velocity of the satellite, and α is the angle between the radar array plane and the satellite velocity.

[0084] S1015. According to the elevation angle θ ELm corresponding to each ambiguity range ring and the azimuth angle θ AZm,i of the i-th clutter scattering cell competing with the target on each ambiguity range ring, calculate the spatial domain steering vector s m,i corresponding to each scattering cell on each ambiguity range ring.

[0085] Here, the spatial domain steering vector s m,i of the i-th clutter scattering cell on each ambiguity range ring is expressed as:

[0086]

[0087] Among them, N represents the number of pulses in a CPI; d represents the distance between adjacent array elements; λ represents the signal wavelength; θ ELm represents the elevation angle of the m-th ambiguity range ring; θ AZm,i represents the azimuth angle of the i-th scattering cell on the m-th ambiguity range ring; [·]T represents the transpose operation; s m represents the spatial domain steering vector of the m-th fuzzy distance ring fuzzy clutter.

[0088] S1016. Determine the spatial domain steering vector of each fuzzy distance ring clutter through the spatial domain steering vector s of all clutter scattering units competing with the target on each fuzzy distance ring m,i Determine the spatial domain steering vector of each fuzzy distance ring clutter.

[0089] Here, the spatial domain steering vector of each fuzzy distance ring fuzzy clutter is expressed as:

[0090]

[0091] where s m,i represents the spatial domain steering vector of the i-th scattering unit on the m-th fuzzy distance ring; L m represents the number of scattering units with the same Doppler frequency as the target in each fuzzy distance ring; a m,i represents the clutter amplitude of the i-th scattering unit on the m-th fuzzy distance ring.

[0092] Exemplarily, the slant range corresponding to the m-th fuzzy distance ring is given by formula (1.2), where M represents the number of ambiguities.

[0093] The elevation angle θ corresponding to each fuzzy distance ring ELm is expressed as formula (1.4).

[0094] The clutter scattering units competing with the target have the same Doppler frequency as the target, so there is: Then the azimuth angle θ corresponding to each clutter scattering unit can be obtained AZm,i as formula (1.5). It should be noted that the earth's rotation is not considered here.

[0095] Then the spatial domain steering vector s of the i-th clutter scattering unit on each fuzzy distance ring m,i is expressed as formula (1.6).

[0096] Then the steering vector s on this ring m is obtained by weighted summation of the contributions of all competing clutter scattering units as formula (1.7).

[0097] Exemplarily, in an example of the present invention, assume that the azimuth angle of the target is θ AZ , and the elevation angle of the target is θ EL , then it can be known that the spatial domain steering vector of the target is expressed as formula (1.1).

[0098] S102. Calculate the included angle corresponding to each ambiguous range ring based on the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector of each ambiguous range ring, and calculate the mean value based on the included angles corresponding to each ambiguous range ring.

[0099] Specifically, in step S102, calculate the included angle corresponding to each ambiguous range ring by using the included angle formula based on the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector of each ambiguous range ring, including:

[0100] Calculate the corresponding included angle by using the included angle formula; where the included angle formula is expressed as:

[0101]

[0102] where, s tar represents the target spatial domain steering vector; s m represents the ambiguous clutter spatial domain steering vector on the m-th ambiguous range ring; represents the conjugate transpose vector of the ambiguous clutter spatial domain steering vector on the m-th ambiguous range ring; ψ m represents the included angle between the m-th ambiguous range ring and the target spatial domain steering vector.

[0103] Exemplarily, in an example of the present invention, calculate the angle deviation between the angle of the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector and find the mean value, and calculate the angle deviation between the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector according to the target competition, and the formula is (1.8).

[0104] S103. Calculate the deviation degree between the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector based on the included angles corresponding to each ambiguous range ring and the mean value;

[0105] Specifically, in step S103, calculate the deviation degree between the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector based on the included angles corresponding to each ambiguous range ring and the mean value, including:

[0106] Calculate the deviation degree between the ambiguous clutter spatial domain steering vector and the target spatial domain steering vector by using the deviation degree calculation formula based on the included angles corresponding to each ambiguous range ring and the mean value; where the deviation degree calculation formula is expressed as:

[0107]

[0108] where, ψ m represents the included angle between the spatial domain steering vector corresponding to all scattering units on the m-th ambiguous range ring and the target spatial domain steering vector; ψ0 represents the mean value of the included angles between the spatial domain steering vector corresponding to all scattering units on the m-th ambiguous range ring and the target spatial domain steering vector; M represents the number of ambiguities; σ represents the deviation degree.

[0109] Exemplarily, in an example of the present invention, the deviation degree of the ambiguous clutter spatial domain steering vector competing with the target from the target spatial domain steering vector is calculated according to the included angle between the calculated ambiguous clutter spatial domain steering vector and the target spatial domain steering vector and its average value, and the deviation degree calculation formula is expressed as formula (1.9).

[0110] S104. Construct an unambiguous clutter covariance matrix in the ideal state according to the unambiguous clutter spatial domain steering vector, and calculate the ideal signal-to-clutter ratio according to the unambiguous clutter covariance matrix, the deviation degree, and the target spatial domain steering vector;

[0111] Specifically, calculating the ideal signal-to-clutter ratio according to the unambiguous clutter covariance matrix, the deviation degree, and the target spatial domain steering vector includes the following steps S1041 to S1043.

[0112] S1041. Solve the inverse matrix of the unambiguous clutter covariance matrix;

[0113] S1042. Calculate the optimal weight vector in the ideal state through the product of the inverse matrix, the target spatial domain steering vector, and the deviation degree;

[0114] S1043. Apply the optimal weight vector to the target signal to calculate the ideal signal-to-clutter ratio.

[0115] Here, the ideal signal-to-clutter ratio is expressed as:

[0116]

[0117] Among them, among them, represents the target power; represents the conjugate transpose vector of the target spatial domain steering vector; represents the inverse matrix of the unambiguous clutter covariance matrix; s tar represents the target spatial domain steering vector.

[0118] Specifically, in step S104, the covariance matrix of the unambiguous clutter in the ideal state is constructed according to the unambiguous clutter spatial domain steering vector s0 competing with the target as:

[0119]

[0120] Among them, CNR represents the clutter-to-noise ratio, represents the noise power, I represents the identity matrix; s0 represents the unambiguous clutter spatial domain steering vector.

[0121] Since R cnIt is only related to the radial velocity and elevation angle of the target. Therefore, an inverse matrix dataset of the clutter covariance matrix can be constructed in advance according to these two variables, so that the inverse matrix of the clutter covariance matrix can be quickly obtained directly according to the two variables when in use.

[0122] In an example of the present invention, according to formula (1.10), the evaluated output SCNR corresponding to the clutter-free target airspace steering vector in the ideal state is obtained.

[0123] S105: Using the target airspace steering vector as the weight vector, the actual signal-to-clutter ratio is obtained, and the target output signal-to-clutter ratio loss is obtained according to the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio.

[0124] Specifically, in step S105, using the target airspace steering vector as the weight vector, the actual signal-to-clutter ratio is obtained, and the target output signal-to-clutter ratio loss is obtained according to the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio, including the following S1051 to S1054.

[0125] S1051: Using the target airspace steering vector as the weight vector, perform STAP filtering on the clutter airspace steering vectors of each ambiguous range ring and calculate the output signal power P;

[0126] S1052: Based on the output signal power P, the actual signal-to-clutter ratio is obtained;

[0127] S1053: Numerically convert the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio respectively to obtain the first ideal signal-to-clutter ratio and the first actual signal-to-clutter ratio;

[0128] S1054: Calculate the target output signal-to-clutter ratio loss according to the first ideal signal-to-clutter ratio and the first actual signal-to-clutter ratio.

[0129] Here, the target output signal-to-clutter ratio loss is expressed as:

[0130] SCNR Loss (dB) = SCNR out (dB) - SNR(dB) (1.12)

[0131] Wherein, SCNR Loss (dB) represents the target output signal-to-clutter ratio loss; SNR(dB) represents the first actual signal-to-clutter ratio; SCNR out (dB) represents the first ideal signal-to-clutter ratio.

[0132] Exemplarily, in an example of the present invention, according to the STAP principle, when uniform array reception is completed, the output signal power after STAP filtering with the target airspace steering vector as the weight vector can be expressed as:

[0133]

[0134] In the formula, s m represents the spatial domain steering vector of all competing clutter scattering cells on the m-th ambiguous range ring, and s tar represents the target spatial domain steering vector, and ( ) H represents taking the conjugate transpose, and sinθ tar = sinθ EL cosθ AZ ; sinθ m = sinθ ELm cosθ AZm ; where θ m is calculated according to the azimuth and elevation angles of the i clutter scattering cells competing with the target on the m-th ambiguous range ring.

[0135] Therefore, when using a uniform array for reception, with the target theoretical steering vector as the weight vector, the amplitude of the beamforming output during the matching beamforming of the space-time steering vectors at different ambiguous range rings is the sinc function. Furthermore, the actual signal-to-clutter ratio can be obtained from the absolute average deviation of the steering vector angle:

[0136]

[0137] where, sinc(·) represents the sinc function, and SCNR out,w represents the actual signal-to-clutter ratio corresponding to the target spatial domain steering vector s tar in the ideal state without ambiguous clutter.

[0138] For the actual signal-to-clutter ratio SCNR out and the ideal signal-to-clutter ratio SCNR out,w , they are respectively converted to obtain the first ideal signal-to-clutter ratio SCNR out (dB) and the first actual signal-to-noise ratio SNR(dB).

[0139] The specific conversion method is: calculate the first ideal signal-to-clutter ratio SCNR out (dB) and the first actual signal-to-noise ratio SNR(dB) according to the specific noise power.

[0140] In an example of the present invention, according to the calculated output SCNR corresponding to the target spatial domain steering vector and the target signal-to-noise ratio, the output signal-to-clutter ratio loss can be obtained, and the calculation formula is formula (1.12).

[0141] On the second aspect, the present invention provides a device for rapidly evaluating the clutter suppression ability based on a space-based bistatic detection system. The device includes: an initialization module, an angle calculation module, a deviation calculation module, an ideal signal-to-clutter ratio calculation module, and an output module.

[0142] An initialization module, configured to obtain a target airspace steering vector and calculate the ambiguous clutter airspace steering vectors of each ambiguous range ring according to the ambiguity situation;

[0143] An included angle calculation module, configured to calculate the included angles corresponding to each ambiguous range ring according to the ambiguous clutter airspace steering vectors and the target airspace steering vector of each ambiguous range ring, and calculate the mean value according to the included angles corresponding to each ambiguous range ring;

[0144] A deviation calculation module, configured to calculate the deviation between the ambiguous clutter airspace steering vector and the target airspace steering vector according to the included angles corresponding to each ambiguous range ring and the mean value;

[0145] An ideal signal-to-clutter ratio calculation module, configured to construct an ideal unambiguous airspace clutter covariance matrix according to the unambiguous airspace clutter steering vector, and calculate the ideal signal-to-clutter ratio according to the unambiguous airspace clutter covariance matrix, the deviation, and the target airspace steering vector;

[0146] An output module, configured to obtain the actual signal-to-clutter ratio with the target airspace steering vector as the weight vector, and obtain the target output signal-to-clutter ratio loss according to the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio.

[0147] The effects of the present invention are further illustrated by the following simulation experiments.

[0148] 1. Simulation conditions

[0149] The simulation experiment of this example takes the spaceborne SAR-GMTI system as an example, and the simulation parameter configuration is as follows: radar carrier frequency 125 MHz, signal bandwidth 2 MHz, pulse repetition frequency 8000 Hz, noise figure 2 dB, receiving and transmitting antenna gain 47.7 dB. The detailed parameters are shown in Table 1.

[0150] Table 1 Radar system parameters

[0151] Parameter Value Radar carrier frequency (unit: MHz) 125 Signal bandwidth (unit: MHz) 2 Pulse repetition frequency (unit: Hz) 8000 Noise figure (unit: dB) 2 Receive and transmit antenna gain (unit: dB) 47.7

[0152] 2. Simulation content and result analysis

[0153] Simulation content:

[0154] In this example, a method for rapidly evaluating the clutter suppression ability under the space-based bistatic detection system provided in the above Embodiment 1 is used to simulate the corresponding output SCNR loss curves of the task-level strict evaluation method and the rapid evaluation method for calculating the weight vector based on covariance matrix estimation under the space-based bistatic system in the case of long-distance detection, so as to verify the accuracy of the rapid evaluation method under long-distance detection.

[0155] Result analysis: Please refer to Figure 2 、 Figure 3 、 Figure 4. Specifically, Figure 2 is a schematic diagram of the angle corresponding to the ambiguous range in the space-based bistatic mode provided by the embodiments of the present invention. The horizontal axis represents the ambiguity order. The larger the ambiguity order, the more serious the range ambiguity problem of the target. The vertical axis represents the grazing angle, which indicates the angle relative to the ground when the radar receives the target echo. The grazing angle decreases as the ambiguity order increases, indicating that the clutter interference closer to the ground is stronger and the ambiguity order is higher. At the same time, the grazing angle changes little with the ambiguity order and is basically linear, indicating that the target angle distribution in different ambiguous range cells is relatively uniform and the distance dependence of the steering vector is weak.

[0156] Figure 3 is a comparison chart of the output SCNR loss curves, showing the change of the SCNR loss after STAP processing with the target radial velocity. Among them, the blue curve represents the corresponding output SCNR loss curve, the red curve is the output SCNR loss curve obtained by using the strict evaluation method when considering ambiguity, and the green curve is the output SCNR loss curve obtained by using the fast evaluation method when considering range ambiguity. It can be seen from the figure that at the far sidelobe, the SCNR losses of the fast evaluation method and the task-level strict evaluation method are close, and the error is small. At the near sidelobe, the difference in the SCNR losses between the two methods is also less than 1 dB. Generally speaking, in the case of long-distance detection, the fast evaluation method can be used to improve the evaluation efficiency of the clutter suppression ability while ensuring the calculation accuracy.

[0157] Figure 4 represents the SNR calculation error of the fast evaluation method and the strict evaluation method under different target radial velocities, quantifying the gap between the two methods. It can be seen from the figure that at the far sidelobe, the errors of the two methods are small, less than 0.6 dB. At the near sidelobe, the difference in the SCNR losses between the two methods is also within 1 dB. Figure 4 Once again, it accurately illustrates that for the space-based bistatic detection system, the fast evaluation method can accurately estimate the SCNR loss, especially when the target ambiguous ranges are evenly distributed, and can be used as an efficient fast evaluation method for clutter suppression ability.

[0158] Figure 5 is a comparison chart of the computational complexities of the fast evaluation method and the strict evaluation method with the change of the equivalent number of array elements N. The fast evaluation method uses the unambiguous ideal clutter covariance matrix in the calculation process. In the actual calculation process, this covariance matrix is stored in advance and there is no need to calculate and invert it again. Its computational complexity is o(N 2 ); The strict evaluation method needs to calculate the clutter covariance matrix and invert it, and its computational complexity is o(N 3), so the computational complexity of the fast evaluation algorithm decreases by N times compared to the strict evaluation method. As can be seen from the figure, as the number of equivalent radar array elements N increases, the difference in computational complexity becomes more obvious. The fast evaluation method is much faster than the strict evaluation method in calculating speed when implementing the evaluation, and can achieve fast evaluation of clutter suppression ability.

[0159] It can be seen from the simulation experiment results that the fast evaluation method for clutter suppression ability provided by the present invention can achieve good accuracy while reducing the amount of computation, and can replace the strict evaluation method to quickly evaluate the clutter suppression ability in the case of long-distance detection.

[0160] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, reference can be made to each other. The key points of each embodiment are 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, and so on.

[0161] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting the present invention; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the present invention.

Claims

1. A method for rapidly evaluating the clutter suppression ability under a space-based bistatic detection system, characterized in that Including: Obtain the target airspace steering vector, and calculate the ambiguous clutter airspace steering vectors of each ambiguous range ring according to the ambiguity situation; Calculate the included angles corresponding to each ambiguous range ring according to the ambiguous clutter airspace steering vectors of each ambiguous range ring and the target airspace steering vector, and calculate the mean value according to the included angles corresponding to each ambiguous range ring; Calculate the deviation degree between the ambiguous clutter airspace steering vector and the target airspace steering vector according to the included angles corresponding to each ambiguous range ring and the mean value; Construct an unambiguous airspace clutter covariance matrix in the ideal state according to the unambiguous airspace clutter steering vector, and calculate the ideal signal-to-clutter ratio according to the unambiguous airspace clutter covariance matrix, the deviation degree and the target airspace steering vector; Use the target airspace steering vector as the weight vector to obtain the actual signal-to-clutter ratio, and obtain the target output signal-to-clutter ratio loss according to the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio.

2. The rapid evaluation method for clutter suppression ability under the space-based bistatic detection system according to claim 1, wherein The calculating the ambiguous clutter airspace steering vectors of each ambiguous range ring according to the ambiguity situation includes: Determine the number of ambiguity distance rings and calculate the slant range R corresponding to each ambiguity distance ring sm ; According to the slant range R corresponding to each ambiguity distance ring sm and the altitude from the satellite to the sub-satellite point, the detection distance R corresponding to each ambiguity distance ring is calculated m ; According to the slant range R corresponding to each ambiguity range ring sm and the detection range R m , the elevation angle θ corresponding to each ambiguity range ring is calculated ELm ; According to the Doppler frequency of the target, calculate the number i of clutter scattering cells competing with the target on each ambiguous range ring and the azimuth angle θ corresponding to each scattering cell AZm,i ; According to the elevation angle θ corresponding to each ambiguous range ring ELm and the azimuth angle θ of the i-th clutter scattering unit competing with the target on each ambiguous range ring AZm,i , the spatial domain steering vector s of each scattering unit on each ambiguous range ring is calculated m,i . Determine the clutter spatial steering vectors of each ambiguous range ring through the spatial steering vectors s of all clutter scattering cells competing with the target on each ambiguous range ring m,i Determine the clutter spatial steering vectors of each ambiguous range ring.

3. The rapid evaluation method for clutter suppression ability under the space-based bistatic detection system according to claim 2, wherein According to the slant range R corresponding to each of the fuzzy distance rings sm and the altitude of the satellite to the sub-satellite point, the detection distance R corresponding to each fuzzy distance ring is calculated m , including: According to the slant range R corresponding to each ambiguity distance ring sm and the height of the satellite to the sub-satellite point, the detection distance R corresponding to each ambiguity distance ring is calculated by using the detection distance calculation formula m ; The detection range calculation formula is expressed as: Among them, R m represents the detection distance corresponding to the m-th ambiguity distance ring; R e represents the radius of the Earth; H represents the height of the satellite from the sub-satellite point; R sm represents the slant range of the m-th ambiguity distance ring; M represents the ambiguity times.

4. The rapid evaluation method for clutter suppression ability under the space-based bistatic detection system according to claim 1, wherein The calculating the included angles corresponding to each ambiguous range ring according to the ambiguous clutter airspace steering vectors of each ambiguous range ring and the target airspace steering vector includes: Calculate the included angles corresponding to each ambiguous range ring according to the ambiguous clutter airspace steering vectors of each ambiguous range ring and the target airspace steering vector by using the included angle formula; Wherein, the included angle formula is expressed as: Among them, s tar represents the target airspace steering vector; s m represents the ambiguous clutter airspace steering vector on the m-th ambiguous range ring; represents the conjugate transpose vector of the ambiguous clutter airspace steering vector on the m-th ambiguous range ring; ψ m represents the angle between the m-th ambiguous range ring and the target airspace steering vector; the value range of m.

5. The rapid evaluation method for clutter suppression ability under the space-based bistatic detection system according to claim 1, characterized in that The calculating the deviation degree between the ambiguous clutter airspace steering vector and the target airspace steering vector according to the included angles corresponding to each ambiguous range ring and the mean value includes: Calculate the deviation degree between the ambiguous clutter airspace steering vector and the target airspace steering vector according to the included angles corresponding to each ambiguous range ring and the mean value by using the deviation degree calculation formula; Wherein, the deviation degree calculation formula is expressed as: where, ψ m represents the angle between the spatial domain steering vectors corresponding to all scattering units on the m-th ambiguous range ring and the target spatial domain steering vector; ψ0 represents the mean value of the angle between the spatial domain steering vectors corresponding to all scattering units on the m-th ambiguous range ring and the target spatial domain steering vector; m ∈ (0, M); M represents the ambiguity order; σ represents the deviation degree.

6. The rapid evaluation method for clutter suppression ability based on the space-based bistatic detection system according to claim 1, wherein The calculating the ideal signal-to-clutter ratio according to the unambiguous airspace clutter covariance matrix, the deviation degree and the target airspace steering vector includes: Solve the inverse matrix of the unambiguous airspace clutter covariance matrix; Perform multiplication through the inverse matrix, the target airspace steering vector and the deviation degree to calculate the optimal weight vector in the ideal state; Act on the target signal with the optimal weight vector to calculate the ideal signal-to-clutter ratio.

7. The rapid evaluation method for clutter suppression ability based on the space-based bistatic detection system according to claim 1, characterized in that The using the target airspace steering vector as the weight vector to obtain the actual signal-to-clutter ratio, and obtaining the target output signal-to-clutter ratio loss according to the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio includes: Use the target airspace steering vector as the weight vector to perform STAP filtering on the ambiguous clutter airspace steering vectors of each ambiguous range ring and calculate the output signal power P; Based on the output signal power P, obtain the actual signal-to-clutter ratio; Perform numerical conversion on the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio respectively to obtain the first ideal signal-to-clutter ratio and the first actual signal-to-clutter ratio; Calculate the target output signal-to-clutter ratio loss according to the first ideal signal-to-clutter ratio and the first actual signal-to-clutter ratio.

8. The rapid evaluation method for clutter suppression ability based on the space-based bistatic detection system according to claim 7, characterized in that The calculating the target output signal-to-clutter ratio loss according to the first ideal signal-to-clutter ratio and the first actual signal-to-clutter ratio is realized through the following formula: SCNR Loss (dB) = SCNR out (dB) - SNR(dB); Among them, SCNR Loss (dB) represents the target output signal-to-noise ratio loss; SNR(dB) represents the first actual signal-to-noise ratio; SCNR out (dB) represents the first ideal signal-to-noise ratio.

9. A device for rapidly evaluating the clutter suppression ability based on a space-based bistatic detection system, characterized in that, Including: An initialization module, which is used to obtain the target airspace steering vector and calculate the ambiguous clutter airspace steering vectors of each ambiguous range ring according to the ambiguity situation; An included angle calculation module, which is used to calculate the included angles corresponding to each ambiguous range ring according to the ambiguous clutter airspace steering vectors of each ambiguous range ring and the target airspace steering vector, and calculate the mean value according to the included angles corresponding to each ambiguous range ring; A deviation calculation module, which is used to calculate the deviation between the ambiguous clutter airspace steering vector and the target airspace steering vector according to the included angles corresponding to each ambiguous range ring and the mean value; An ideal signal-to-clutter ratio calculation module, which is used to construct an ideal unambiguous airspace clutter covariance matrix according to the unambiguous airspace clutter steering vector, and calculate the ideal signal-to-clutter ratio according to the unambiguous airspace clutter covariance matrix, the deviation and the target airspace steering vector; An output module, which is used to obtain the actual signal-to-clutter ratio with the target airspace steering vector as the weight vector, and obtain the target output signal-to-clutter ratio loss according to the ideal signal-to-clutter ratio and the actual signal-to-clutter ratio.

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