CN114740434B - Equidistant distributed subarray system and method for resisting accompanying interference - Google Patents
Equidistant distributed subarray system and method for resisting accompanying interference Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The invention discloses a method for resisting accompanying-flight interference of an equidistantly distributed subarray, which belongs to the technical field of radar signals and information processing, and comprises the steps of firstly, inhibiting side lobe interference and reserving main lobe interference and target signals by applying a side lobe interference zero setting technology containing MLM constraint on the subarray; secondly, detecting the target and the interference signal in the main lobe by using an optimization method based on sparsity of the main lobe target and the interference signal among subarrays, and realizing separation of the target and the interference signal; finally, the FA technology and the angular coordinate de-blurring algorithm based on coordinate clustering are comprehensively applied, and the target angle estimation is achieved. The method provided by the invention has higher target and interference resolving power, target detection capability and angle estimation precision under the main lobe interference scene through theoretical deduction and simulation analysis.
Description
Technical Field
The invention belongs to the technical field of radar signal and information processing, and particularly relates to an equidistant distributed subarray system and a method for resisting accompanying interference.
Background
The fly-by disturbance (problem P1) is usually generated by a towed or thrown active disturbance device, the disturbance carrier of which is usually co-located with the fighter plane within the main lobe and with a certain angular difference. The main lobe interference cancellation technology (MLC) is used to control the antenna pattern to form notch in the main lobe interference direction, so as to realize zero setting of the interference gain. However, in the air-to-electronic countermeasure process, the fighter can effectively compress the angle difference between the fighter and the interference equipment by using tactical and technical means, so that the fighter is also positioned in the notch direction of the main lobe pattern, and the radar system greatly reduces the detection and tracking performance of the fighter. If the antenna system adopts a large array antenna, the width of the main lobe notch is obviously reduced, and when the aperture of the antenna is large enough, the main lobe notch does not cover the direction of a fighter any more, so that the radar system can realize the detection and tracking of the fighter. However, the construction of the large array antenna by using the sparse aperture technology has the characteristics of large array element number and difficult maneuvering, and the design requirement of the vehicle-mounted radar is difficult to meet.
As known from the existing sparse array optimization algorithms, the algorithms optimize the main lobe, the side lobe level and the array sparsity, inhibit grating lobes of an antenna directional pattern, the antenna gain of the grating lobe-free directional pattern in the main lobe direction is far higher than that of other directions, and the characteristics are used for target detection, so that the problem of angle ambiguity cannot occur, and the type of antenna can easily determine the target direction. However, for the same main lobe width, grating lobe-free arrays typically require more antenna elements than grating lobe-containing arrays, and for large array antennas (apertures up to tens of meters or more), the difference in the number of elements of the two array patterns becomes particularly pronounced. In order to further reduce the number of array elements in the antenna system, we propose an equidistant sub-array anti-fly-by interference technique.
Equidistantly distributed sub-arrays (uniformly distributed sub arrays, UDSA) are a typical array pattern where the sub-arrays within the system are arranged to have the same array structure and the sub-array pitch is much larger than half-waves. According to the array signal processing theory, when each array element of the system has the same directional diagram, the synthesized directional diagram of the system has a main lobe and a plurality of grating lobes, and the grating lobe distribution of the system has stronger regularity. Further analysis shows that the main lobe width of the system is determined by the total span of the main lobe, and under the condition that the number of subarrays of the system is fixed, the resolution capability of the main lobe can be improved by increasing the subarray distance, and the characteristic has important significance for resolving targets in the main lobe from accompanying interference signals. However, as the sub-array pitch increases (total spans up to tens of meters) the system will face several technical problems that need to be addressed: firstly, the traditional narrow-band radar signal does not maintain the narrow-band characteristic on a large-scale array, namely, the guide vectors of all frequency points in a target echo frequency band are not identical, so that the system needs to preprocess all paths of received signals in a time-frequency domain to ensure that the system meets the limitation of a distributed antenna on the signal bandwidth; secondly, in order to ensure that the grating lobe regularity of the system is not destroyed in the external interference suppression process, the system needs to design the same interference suppression filter on each subarray to filter out side lobe interference, and needs to ensure that main lobe interference and a target acquire enough gain; finally, the array pattern grating lobes can lead to ambiguous angular measurements, requiring a corresponding solution to be given.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides an equidistant distributed subarray system and a method for resisting accompanying interference.
A first object of the present invention is to provide a method for equally distributing sub-arrays against accompanying interference, comprising the steps of:
S1, performing time-frequency domain preprocessing and filtering on target echo and a plurality of interference signals input by each antenna in an equidistant distributed subarray system to the same narrow-band range, so that the input signals of the system meet the narrow-band condition, and a target guide vector with the direction theta in the narrow-band range can be expressed as follows:
Wherein, Denoted Kronecher product, ad (sin θ) denotes an inter-subarray steering vector, as (sin θ) denotes an intra-subarray steering vector, and a d (sin θ) and a s (sin θ) can be expressed as:
wherein θ is an angle, λ is a wavelength of a detection signal, d is an array element pitch, L is an array pitch, M is the number of subarrays, and N is the number of array elements on the subarrays;
S2, performing spatial filtering processing on the preprocessed target echo and the preprocessed interference signals in the step S1, inputting the processed target echo and the processed interference signals into subarrays in an equidistant distributed subarray system, suppressing the side lobe interference of each subarray by using the same side lobe interference suppression filter, keeping the shape of a main lobe in the suppression process, and after each subarray filters the side lobe interference, expressing the output target echo and the interference signals as follows:
Wherein w SLC is a subarray spatial filter, I M×M is a unit matrix, z d is a sidelobe canceller output signal, and z is a sidelobe canceller input signal;
S3, detecting target signals by using a sparse detection model on the target echo and a plurality of interference signals output in each step S2 among subarrays, and solving the target signals by using the following optimization method:
Wherein Φ is a sensing matrix, Φ= [ a d(sinθ0),ad(sinθ1),…,ad(sinθI-1) ], the guiding vector a d (sin θ) takes λ/L as a period in sin θ domain, in order to avoid the repetition of sensing matrix array vectors, I guiding vectors are taken in one period, and the angle θi corresponding to each vector satisfies the following relationship:
θi＝arcsinξi，
ξi＝ξ0+iΔ，0≤i≤I-1，
Wherein, theta 0 is the center direction of the subarray beam, xi 0＝sinθ0 corresponds to the reference sine value pointed by the beam center, each angle sine value xi i forms an arithmetic array, the difference value is delta, wherein I is the angle sampling number, lambda is the wavelength, and the range of the non-fuzzy measurement interval is theta epsilon [ theta 0,θu ], wherein
S4, measuring the angle x of the same target obtained in the step S3 on different carrier frequencies for a plurality of times through a Frequency Agility (FA) technology, and obtaining respective remainder, wherein the relation between remainder sets corresponding to different carrier frequencies meets the following congruence equation set:
Wherein K represents the number of different carriers in the FA process, and I k is the number of non-fuzzy angle samples;
s5, processing the target angle coordinate x k in the step S4 based on a fuzzy coordinate clustering algorithm to obtain a target coordinate mean value.
Preferably, in step S1, the time-frequency domain preprocessing includes the following steps:
A group of distance gating signals which are adjacent to each other and cover a full distance section are respectively arranged for each antenna receiver in the equidistant distribution subarray system, the width of each distance gating signal is set according to the distance resolution of a radar, a narrow-band filter is correspondingly arranged for each distance gating signal, each narrow-band filter works at the same frequency point, when the speed of a target concerned is unknown, the frequency point is arranged at a zero Doppler frequency shift, when an estimated value exists for the speed, the frequency point is arranged at a corresponding Doppler frequency shift, and target echoes insensitive to the Doppler frequency shift and a plurality of interference signals received by each antenna receiver are filtered to the same narrow-band range through the corresponding distance gating signals and the narrow-band filters.
Preferably, in step S1, the time-frequency domain preprocessing includes the following steps:
A group of distance gating signals which are adjacent to each other and cover the whole distance section are respectively arranged for each antenna receiver in the equidistant distribution subarray system, the width of each distance gating signal is set according to the distance resolution of a radar, a group of filter groups are correspondingly arranged for each distance gating signal, the frequency coverage range of each filter group is the same as the fuzzeless frequency measurement range of a target signal, and target echo and a plurality of interference signals which are received by each antenna receiver and are sensitive to Doppler frequency shift are filtered to the same narrow-band range through the corresponding distance gating signals and narrow-band filters.
Preferably, in step S2, the spatial filtering process includes the following steps: and (3) windowing the spatial filters in the equidistant distributed sub-array system, wherein the preprocessed target echo and a plurality of interference signals in the step S1 are subjected to spatial filtering through the spatial filters subjected to windowing.
Preferably, in step S2, the sidelobe interference suppression filter is designed by an optimization model with an infinite norm minimization, the optimization model uses a constraint condition that a unit gain is formed in a target direction and a zero gain is formed in a sidelobe interference direction, and uses a minimum level of a sidelobe as a target function, and a mathematical expression thereof is as follows:
Where θc is the desired target direction, θj is the interference signal direction, aj is the side lobe interference direction angle coordinate set, and As is the preset side lobe direction angle sampling set.
Preferably, in step S5, the processing method of the fuzzy coordinate clustering algorithm for the target angular coordinate x k,p is as follows:
s51, presetting carrier frequencies to enable the moduli Ik (k=1, 2, & K) corresponding to the carrier frequencies in the step S4 to be mutually prime, and expanding a non-fuzzy angle measurement range to be Performing sparse detection on K different carrier frequencies according to a sparse detection model to obtain a group of coordinate remainder r 1,r2,···,rK;
S52, in a non-fuzzy angle measurement range, the target angle coordinates corresponding to any remainder r k are x k1,xk2,···,xkpk respectively, wherein x kp＝rk+(p-1)Ik;
S53, setting the initial value n=0 of the iteration times, setting the initial positions of the target angles associated with the carrier frequencies as x k(n)＝rk,k1, 2, K, and calculating a clustering cost function of the target coordinates,
By searching the cluster cost function minimum, a target angle value may be determined.
A second object of the present invention is to provide an equidistantly distributed sub-array system, which is composed of M sub-arrays, the distance between the arrays is L, each sub-array has N omni-directional antenna elements distributed equidistantly, the distance is d, and the carrier wavelength of the system is λ.
Compared with the prior art, the invention has the beneficial effects that:
(1) The method for resisting the accompanying interference of the equidistantly distributed subarrays can effectively improve the resolution capability of the system by increasing the spacing of the subarrays of the system under the condition of fixed number of antenna units, and the characteristic provides an economic solution for resisting the accompanying interference adjacent to a target;
(2) The method has higher target and interference resolving power, target detection capability and angle estimation accuracy under the main lobe interference scene.
Drawings
FIG. 1 is a schematic diagram of preprocessing in which a target signal and an interference signal are Doppler shift insensitive signals;
FIG. 2 is a schematic diagram of preprocessing of a target signal and an interference signal as a Doppler shift sensitive signal in an embodiment of the present invention;
FIG. 3 is a graph of correlation coefficients of a matrix correlation coefficient μ (Φ) and a Gaussian noise matrix of a sparse detection algorithm;
wherein, the matrix correlation coefficient mu (phi) is a diamond mark point, and the correlation coefficient of the Gaussian noise matrix is a box line drawing point drawn by a hollow box and a cross;
FIG. 4 is a schematic diagram of angle measurement ambiguity and disambiguation of UDSA systems in accordance with an embodiment of the present invention;
FIG. 5 is a diagram of a UDSA signal processing system in an embodiment of the present invention;
Fig. 6 is an antenna pattern for ULA and UDSA;
FIG. 7 is a graph of ULA system and UDSA system target versus interference steering vector correlation coefficients;
FIG. 8 is a graph comparing theoretical performances of ULA and UDSA;
FIG. 9 is a plot of main lobe distortion for different sidelobe canceling methods;
FIG. 10 is a graph comparing simulation performance of four UDSA system parameters to simulate a sparse detection algorithm;
FIG. 11 is a graph comparing the performance ROC curves of MSJNR, MESE and sparse detection methods under different SNR conditions;
Fig. 12 is an angular coordinate estimation performance chart.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
A method for resisting accompanying interference of an equidistantly distributed subarray specifically comprises the following steps:
S1, performing time-frequency domain preprocessing and filtering on target echo and a plurality of interference signals input by each antenna in an equidistant distributed subarray system to the same narrow-band range, so that the input signals of the system meet the narrow-band condition, and a target guide vector with the direction theta in the narrow-band range can be expressed as follows:
Wherein, Denote Kronecher products, ad (sin theta) denotes the inter-subarray steering vector, as (sin theta) denotes the intra-subarray steering vector, and both can be expressed as
Wherein θ is an angle, λ is a wavelength of a detection signal, d is an array element pitch, L is an array pitch, M is the number of subarrays, and N is the number of array elements on the subarrays;
according to the frequency band characteristics of the radar detection signals, the target echo and a plurality of interference signals can be divided into a Doppler shift insensitive signal and a Doppler shift sensitive signal, and the preprocessing methods of the two signals are respectively analyzed as follows:
when the target echo and the plurality of interference signals are Doppler shift insensitive signals, the time-frequency domain preprocessing flow is shown in fig. 1, and specifically includes the following steps:
A group of distance gating signals which are adjacent to each other and cover a full distance section are respectively arranged for each antenna receiver in the equidistant distribution subarray system, the width of each distance gating signal is set according to the distance resolution of a radar, a narrow-band filter is correspondingly arranged for each distance gating signal, each narrow-band filter works at the same frequency point, when the target speed of interest is unknown, the frequency point is arranged at a zero Doppler frequency shift, when an estimated value exists in the speed, the frequency point is arranged at the corresponding Doppler frequency shift, target echo insensitive to the Doppler frequency shift and a plurality of interference signals received by each antenna receiver are filtered to the same narrow-band range through the corresponding distance gating signals and the narrow-band filters, and the signal processing method ensures the narrow-band receiving condition of the system while ensuring the distance resolution. Meanwhile, the signal pattern is insensitive to Doppler frequency shift, so that the signals with different Doppler frequency shifts are guaranteed to have detection capability.
When the target echo and the plurality of interference signals are Doppler frequency shift sensitive signals, although the frequency band coverage range (comb spectrum envelope width) of the 'PC+MTD' and 'PD' system radars is difficult to meet the 'narrowband condition', the single spectral line of the 'PC+MTD' system radars is narrowband, so that the signal processing architecture shown in fig. 2 is used for extracting the single spectral line to realize narrowband processing, and the time-frequency domain preprocessing specifically comprises the following steps:
A group of distance gating signals which are adjacent to each other and cover the whole distance section are respectively arranged for each antenna receiver in the equidistant distribution subarray system, the width of each distance gating signal is set according to the distance resolution of a radar so as to ensure the distance resolution and the whole coverage capacity of the acting distance, a group of filter groups are correspondingly arranged for each distance gating signal, the frequency coverage range of each filter group is the same as the non-fuzzy frequency measurement range of a target signal so as to ensure that the detection capacity is realized for various Doppler frequency shifts, and target echo sensitive to the Doppler frequency shift and a plurality of interference signals received by each antenna receiver are filtered to the same narrow-band range through the corresponding distance gating signals and the narrow-band filter.
S2, in order to reduce side lobe levels, spatial filtering processing is carried out on the preprocessed target echo and the interference signals in the step S1, specifically, windowing processing is carried out on the spatial filters in the equal-distance distribution sub-array system, and spatial filtering processing is carried out on the preprocessed target echo and the interference signals in the step S1 through the spatial filters subjected to windowing processing. Then, the processed target echo and a plurality of interference signals are input into each subarray in the equidistant distributed subarray system, if an adaptive filter (such as a Capon filter) is used for external interference suppression, the filter forms notches in each interference direction, when main lobe interference exists outside, the adaptive filter notches change the shape of the main lobe and lead to the reduction of target gain, in order to keep the gain of the main lobe to the target, each subarray uses the same sidelobe interference suppression filter for suppressing the sidelobe interference of each subarray, the main lobe is conformal in the suppression process, and after each subarray filters out the sidelobe interference, the output target echo and a plurality of interference signals can be expressed as follows:
The sidelobe interference suppression filter is obtained by designing an optimization model with minimum infinity norm, the optimization model takes a constraint condition that a target direction forms a unit gain and a sidelobe interference direction forms a zero gain, and takes the minimum sidelobe highest level as a target function, and the mathematical expression is as follows:
Wherein, thetac is the expected target direction, aj is the side lobe interference direction angle coordinate set, as is the preset side lobe direction angle sampling set, and the optimization model can obtain the global optimal solution by a convex optimization method under the condition that the array structure and the side lobe interference direction are estimated;
s3, research shows that under the background of accompanying-flight interference, the targets and main lobe interference signal guide vectors in the equidistant distributed subarray system show weak correlation, so that the z d signal targets and interference have sparse characteristics, and based on the characteristics, target signal detection is realized on target echoes and a plurality of interference signals output in each step S2 between subarrays through a sparse detection model, and the target signal detection is solved by using the following optimization method:
Wherein Φ is a sensing matrix, Φ= [ a d(sinθ0),ad(sinθ1),…,ad(sinθI-1) ], the guiding vector a d (sin θ) takes λ/L as a period in sin θ domain, in order to avoid the repetition of sensing matrix array vectors, I guiding vectors are taken in one period, and the angle θi corresponding to each vector satisfies the following relationship:
wherein Φ is a sensing matrix, Φ= [ a d(sinθ0),ad(sinθ1),…,ad(sinθI-1) ], the steering vector ad (sin θ) takes λl as a period in sin θ domain, in order to avoid the repetition of sensing matrix array vectors, I steering vectors are taken in one period, and the angle θi corresponding to each vector satisfies the following relationship:
θi＝arcsinξi，
ξi＝ξ0+iΔ，0≤i≤I-1，
Wherein θ 0 is the center pointing of the subarray beam, ζ 0＝sinθ0 corresponds to the reference sine value pointed by the beam center, each angle sine value ζ i forms an arithmetic series, the difference is Δ, wherein I is the angle sampling number, λ is the wavelength, and the range of the non-fuzzy measurement interval is θ ε [ θ 0,θu ], wherein
For a sparse detection model, the solvability of the sparse detection model can be ensured by the following formula
Where k is the number of detectable signals and the matrix correlation coefficient μ (Φ) characterizes the correlation between the Φ column vectors of the matrix;
s4, when the array spacing L of the UDSA system is large, the non-fuzzy angle measurement interval of the sparse detection model is far smaller than the width of the main lobe of the subarray, so that for a target echo signal with the angle theta x in the main lobe of the subarray (theta x satisfies sin theta x=sin theta r+qlambda L,0 is less than or equal to r < I, q epsilon Z), the angle calculated by the sparse detection model is thetar, wherein r is the remainder of x with respect to I: x≡r (mod I),
Therefore, when the detection algorithm is used for positioning the target, the sparse detection algorithm solves the same remainder r for different q values, namely the problem of angle measurement ambiguity, in order to eliminate the angle measurement ambiguity, the angle thetax of the same target echo signal obtained in the step S3 is measured for multiple times on different carrier frequencies through the FA technology and respective remainder is obtained, the relationship between the sets of remainders corresponding to different carrier frequencies satisfies x k,p≡rk(modIk), wherein K is {1,2, ···, K }, p is {1,2, for different I k, the corresponding angular coordinate remainder can be obtained and a set of congruence equations formed as follows:
Wherein K represents the number of different carriers in the FA process, and I k is the number of non-fuzzy angle samples; the ambiguity of angular measurement of UDSA system and its principle of deblurring are shown in fig. 4, from which it can be seen that there is a measured value for each coordinate set at the coordinate position corresponding to the real target. Therefore, in the single-value measurement range of the multi-carrier frequency system, the true value point is the 'condensation point' of the coordinates of each coordinate set, the rest points in the coordinate set are the 'divergence points', and in order to calculate the condensation point, the coordinate condensation variance is selected as an objective function;
S5, processing the target angle coordinate x k,p in the step S4 based on a fuzzy coordinate clustering algorithm to obtain a target coordinate mean value, wherein the processing method of the fuzzy coordinate clustering algorithm on the target angle coordinate x k,p is specifically as follows:
s51, presetting carrier frequencies to enable the moduli Ik (k=1, 2, & K) corresponding to the carrier frequencies in the step S4 to be mutually prime, and expanding a non-fuzzy angle measurement range to be Performing sparse detection on K different carrier frequencies according to a sparse detection model to obtain a group of coordinate remainder r 1,r2,···,rK;
S52, in a non-fuzzy angle measurement range, the target angle coordinates corresponding to any remainder r k are x k1,xk2,···,xkpk respectively, wherein x kp＝rk+(p-1)Ik;
S53, setting the initial value n=0 of the iteration times, setting the initial positions of the target angles associated with the carrier frequencies as x k(n)＝rk,k1, 2, K, and calculating a clustering cost function of the target coordinates,
By searching the cluster cost function minimum, a target angle value may be determined.
As shown in fig. 5, the embodiment of the present invention further provides a signal processing system with equally distributed sub-arrays, which is composed of M sub-arrays, where the distance between each array is L, each sub-array has N omni-directional antenna elements that are equally distributed, the distance between each sub-array is d, the carrier wavelength of the system is λ, and the distance between the target/interference and the signal processing system is greater than the system span.
When the spatial filter in UDSA system provided by the embodiment of the invention is windowed, the main lobe width is widened after windowing, but the grating lobe spacing is unchanged. Using taylor window control pattern side lobes herein results in the UDSA antenna system and ULA antenna system patterns (antenna parameters set according to table 1) as shown in fig. 6.
Table 1 ULA and UDSA array parameters
By comparison, the UDSA system can obtain a narrower main lobe width than the ULA system under the condition that the number of antenna array elements is equal. Thus, UDSA systems can increase the resolution of the target and interference by increasing the array pitch (where resolution increase does not require an increase in antenna elements, but only an increase in the number of grating lobes of the array).
In order to analyze that the signal processing system (UDSA system) of the equidistantly distributed subarray provided by the embodiment of the invention can reach theoretical performance, the optimal filtering performance and the spatial spectrum estimation performance lower bound (CRB) of the system and the ULA system provided by the embodiment of the invention under the main lobe accompanying-flight interference background are respectively analyzed.
From analysis, the main lobe filtering performance of the array antenna is mainly determined by the correlation between main lobe interference and a target steering vector.
The target correlation coefficients of the ULA and UDSA systems were calculated using the parameters shown in table 1, and the results are shown in fig. 7. From this figure, it can be seen that the steering vector correlation coefficient of UDSA system is much smaller than that of ULA system when the interfering signal approaches the target, so that UDSA system can obtain higher signal-to-noise ratio in the process of resisting the accompanying interference. However, the UDSA system produces a large correlation peak in several directions when the interfering signal is far from the target, and the UDSA system output signal-to-interference-and-noise ratio will drop significantly when the interfering signal is at the angle of the correlation peak.
By analyzing the vector-directed correlation coefficient expression, the position of the correlation peak is related to the carrier wavelength λ, so that when the actual UDSA system in the embodiment of the present invention is designed, the spatial detection and spatial filtering are implemented by using a set of different carrier wavelengths, thereby effectively avoiding the correlation peak.
The upper and lower sub-graphs of fig. 7 (b) show the positions of correlation peaks for the same UDSA array at different carrier wavelengths, respectively. According to the graph, when the carrier wave wavelength is changed, the relative peak position is correspondingly changed, and for a given group of carrier waves, the interference and the target show weak correlation only under the action of one carrier wave wavelength, so that the system can obtain higher signal-to-interference-and-noise ratio, and the target detection is realized.
The weak correlation characteristic of UDSA system targets and interfering signal steering vectors makes it possible to combat main lobe fly-by interference. The parameters shown in Table 1 are calculated to obtain the maximum signal-to-interference-and-noise ratio of the output signals of UDSA system and ULA system and the CRB of the spatial spectrum estimation. Fig. 8 shows the relationship between the theoretical performance of the two systems and the interference direction when the target direction is fixed, from which it can be seen that UDSA has a better theoretical performance in dealing with the satellite interference problem.
In addition, we also compare the processing effect of the sidelobe interference suppression filter in the step S2 with the effect of the interference suppression processing in the step S2 without adopting the sidelobe interference suppression filter processing and adopting the MSJNR method, and the two interference suppression patterns are shown in fig. 9 (a) and fig. 9 (b), respectively, which show that the interference suppression method based on the optimization model in the step S2 in the embodiment of the invention can effectively ensure that the main lobe of the antenna is not deformed, and the pattern has a lower side lobe level, which is not possessed by the MSJNR method.
In order to evaluate the working performance of the method and the system provided by the embodiment of the invention, the target resolution performance, the target detection performance and the angle estimation performance of the method and the system under the main lobe interference background are respectively simulated. UDSA system antenna configuration parameters and their corresponding theoretical performance parameters are shown in table 2. According to simulation requirements, it is assumed here that the antenna far field has one target, two main lobes active interference, two side lobes active interference, the antenna main lobe points to 5 ° direction, the target angle coordinates are set to 3.2885 °, and the interference angle coordinates are set to-18.3187 °,3.2407 °,3.3244 ° and 15.1114 °, respectively. The radar detection waveform transmitted by the system is simple pulse, and each interference signal waveform is mutually independent Gaussian white noise.
Table 2 system parameter settings
Effect of UDSA System array spacing on resolution Performance
For the same target and interference environment, the signals received by the system will exhibit different sparsity when the antenna array spacing is different. The signal-to-noise ratio of the target echo is set to be snr=20 dB, the dry-to-noise ratio of the interference signal is set to be jnr=25 dB, and the sparse detection algorithm is simulated according to four UDSA system parameters shown in table 2, so that the detection result shown in fig. 10 can be obtained, and fig. 10 shows that the resolving power of the system on the interference of the target and the main lobe can be effectively improved by increasing the space between the subarrays of the UDSA system.
UDSA System detection Performance
To evaluate the target detection performance of UDSA systems, MSJNR, maximum entropy spectrum estimation (maximum entropy spectrum estimation, MESE) and the methods presented herein were used to detect targets, respectively, under the IV set of system parameters shown in table 2. The system uses the above detection method to make 5000 Monte Carlo simulations under different signal-to-noise ratio conditions, respectively, and FIG. 11 shows a receiver operation duration (receiver operating characteristic, ROC) curve showing the relationship between the detection probability Pd and the false alarm probability Pf under different SNR conditions. These curves show that both our proposed method and MSJNR method have better performance under the condition of low signal-to-noise ratio snr= -8dB, while the detection performance of our proposed method is better than the rest methods when snr= -5dB, snr= -2dB and sn=1 dB.
UDSA System Angle estimation Performance
In order to evaluate the angle estimation performance of UDSA systems, the array parameters and carrier wavelengths are set according to the system parameters of the III th group and the IV th group shown in table 2, respectively, and simulation analysis is performed on the angle estimation performance. Under different signal-to-noise ratio conditions, the target angle is estimated by using an angle coordinate solution blurring algorithm, and fig. 12 (a) - (c) show the solution blurring success probability, the error mean value and the error variance (including the variance lower bound, i.e., CRB) of the angle estimation algorithm, respectively. According to the graph, the angle solution blurring algorithm based on the coordinate clustering can effectively solve the problem of angle measurement blurring under the main lobe interference background, and the angle estimation precision gradually approaches to the CRB of the system angle estimation along with the improvement of the signal-to-noise ratio of the target echo.
In summary, in the method for resisting the fly-by interference of the equidistantly distributed subarrays provided by the embodiment of the invention, under the condition that the number of the antenna units is fixed, the resolution capability of the system can be effectively improved by increasing the spacing between the subarrays of the system, and the characteristic provides an economic solution for resisting the fly-by interference adjacent to the target; and the method has higher target and interference resolving power, target detection capability and angle estimation accuracy in a main lobe interference scene.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
Claims (7)
1. The method for resisting the accompanying interference of the subarray in equidistant distribution is characterized by comprising the following steps of:
S1, performing time-frequency domain preprocessing and filtering on target echo and a plurality of interference signals input by each antenna in an equidistant distributed subarray system to the same narrow-band range, so that the input signals of the system meet the narrow-band condition, and a target guide vector with the direction theta in the narrow-band range can be expressed as follows:
Wherein, Denoted Kronecher products, a d (sin θ) denotes an inter-subarray steering vector, a s (sin θ) denotes an intra-subarray steering vector, and a d (sin θ) and a s (sin θ) may be expressed as:
wherein θ is an angle, λ is a wavelength of a detection signal, d is an array element pitch, L is an array pitch, M is the number of subarrays, and N is the number of array elements on the subarrays;
S2, performing spatial filtering processing on the preprocessed target echo and the preprocessed interference signals in the step S1, inputting the processed target echo and the processed interference signals into subarrays in an equidistant distributed subarray system, suppressing the side lobe interference of each subarray by using the same side lobe interference suppression filter, keeping the shape of a main lobe in the suppression process, and after each subarray filters the side lobe interference, expressing the output target echo and the interference signals as follows:
Wherein w SLC is a subarray spatial filter, I M×M is a unit matrix, z d is a sidelobe canceller output signal, and z is a sidelobe canceller input signal;
S3, detecting target signals by using a sparse detection model on the target echo and a plurality of interference signals output in each step S2 among subarrays, and solving the target signals by using the following optimization method:
Wherein Φ is a sensing matrix, Φ= [ a d(sinθ0),ad(sinθ1),…,ad(sinθl-1) ], the guiding vector a d (sin θ) takes λ/L as a period in sin θ domain, in order to avoid the repetition of sensing matrix array vectors, I guiding vectors are taken in one period, and the angle θi corresponding to each vector satisfies the following relationship:
θi＝arcsinξi，
ξi＝ξ0+iΔ，0≤i≤I-1，
Wherein, theta 0 is the center direction of the subarray beam, xi 0＝sinθ0 corresponds to the reference sine value pointed by the beam center, each angle sine value xi i forms an arithmetic array, the difference value is delta, wherein I is the angle sampling number, lambda is the wavelength, and the range of the non-fuzzy measurement interval is theta epsilon [ theta 0,θu ], wherein
S4, measuring the angle x of the same target obtained in the step S3 on different carrier frequencies for a plurality of times through a Frequency Agility (FA) technology, and obtaining respective remainder, wherein the relation between remainder sets corresponding to different carrier frequencies meets the following congruence equation set:
Wherein K represents the number of different carriers in the FA process, and I k is the number of non-fuzzy angle samples;
s5, processing the target angle coordinate x k in the step S4 based on a fuzzy coordinate clustering algorithm to obtain a target coordinate mean value.
2. The method for resisting fly-by interference of equidistantly distributed subarrays according to claim 1, wherein in step S1, the time-frequency domain preprocessing comprises the steps of:
A group of distance gating signals which are adjacent to each other and cover a full distance section are respectively arranged for each antenna receiver in the equidistant distribution subarray system, the width of each distance gating signal is set according to the distance resolution of a radar, a narrow-band filter is correspondingly arranged for each distance gating signal, each narrow-band filter works at the same frequency point, when the speed of a target concerned is unknown, the frequency point is arranged at a zero Doppler frequency shift, when an estimated value exists for the speed, the frequency point is arranged at a corresponding Doppler frequency shift, and target echoes insensitive to the Doppler frequency shift and a plurality of interference signals received by each antenna receiver are filtered to the same narrow-band range through the corresponding distance gating signals and the narrow-band filters.
3. The method for resisting fly-by interference of equidistantly distributed subarrays according to claim 1, wherein in step S1, the time-frequency domain preprocessing comprises the steps of:
A group of distance gating signals which are adjacent to each other and cover the whole distance section are respectively arranged for each antenna receiver in the equidistant distribution subarray system, the width of each distance gating signal is set according to the distance resolution of a radar, a group of filter groups are correspondingly arranged for each distance gating signal, the frequency coverage range of each filter group is the same as the fuzzeless frequency measurement range of a target signal, and target echo and a plurality of interference signals which are received by each antenna receiver and are sensitive to Doppler frequency shift are filtered to the same narrow-band range through the corresponding distance gating signals and narrow-band filters.
4. The method for resisting fly-away interference of equidistantly distributed subarrays according to claim 1, wherein in step S2, said spatial filtering process comprises the steps of: and (3) windowing the spatial filters in the equidistant distributed sub-array system, wherein the preprocessed target echo and a plurality of interference signals in the step S1 are subjected to spatial filtering through the spatial filters subjected to windowing.
5. The method for resisting fly-away interference according to claim 1, wherein in step S2, the sidelobe interference suppression filter is designed by an optimization model with infinite norm minimization, the optimization model uses a constraint condition that a unit gain is formed in a target direction and a zero gain is formed in a side lobe interference direction, and uses a minimum level of a side lobe as a target function, and the mathematical expression is as follows:
Where θc is the desired target direction, θj is the interference signal direction, aj is the side lobe interference direction angle coordinate set, and As is the preset side lobe direction angle sampling set.
6. The method for resisting accompanying interference of equidistantly distributed subarrays according to claim 1, wherein in step S5, the processing method of the fuzzy coordinate clustering algorithm for the target angular coordinate x k,p is as follows:
s51, presetting carrier frequencies to enable the moduli Ik (k=1, 2, & K) corresponding to the carrier frequencies in the step S4 to be mutually prime, and expanding a non-fuzzy angle measurement range to be Performing sparse detection on K different carrier frequencies according to a sparse detection model to obtain a group of coordinate remainder r 1,r2,···,rK;
S52, in a non-fuzzy angle measurement range, the target angle coordinates corresponding to any remainder r k are x k1,xk2,···,xkpk respectively, wherein x kp＝rk+(p-1)Ik;
S53, setting the initial value n=0 of the iteration times, setting the initial positions of the target angles associated with the carrier frequencies as x k(n)＝rk,k1, 2, K, and calculating a clustering cost function of the target coordinates,
By searching the cluster cost function minimum, a target angle value may be determined.
7. An equidistantly distributed sub-array system according to any of claims 1-6, characterized in that it consists of M sub-arrays, the distance between the arrays being L, each sub-array having N equidistantly distributed omni-directional antenna elements with a spacing d and the carrier wavelength of the system being λ.
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