CN115236598B - Subspace distance extension target detection method based on polarized radar - Google Patents
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Abstract
According to the subspace distance extended target detection method based on the polarized radar, provided by the invention, the target detection is carried out by combining echo data of two polarized channels, and the detection performance is improved by using different polarization characteristics of sea clutter and targets; meanwhile, the oblique symmetry characteristic of the sea clutter is added into target detection, and echo data is converted by using a unitary matrix, so that dependence on the number of auxiliary units is reduced by using priori information of the clutter covariance matrix, and the detection performance under the heterogeneous sea clutter background is improved.
Description
Technical Field
The invention belongs to the technical field of signal processing, and particularly relates to a subspace distance extension target detection method based on a polarized radar.
Background
The detection technology of weak targets under the complex space-time variant sea clutter background is a critical difficult problem to be solved in the sea radar detection. In addition to the fact that high-resolution sea clutter generally shows non-stationary, non-uniform and non-Gaussian characteristics, the high-resolution radar also breaks down targets into a plurality of scattering centers and enables finer observation of motion states of all parts, and the space-time variation characteristics of the sea clutter and the double expansion phenomenon of the targets in the distance and Doppler dimensions make detection of weak targets difficult.
Aiming at the problem of detecting the distance expansion target in the sea clutter background, a common method is an adaptive matched filtering technology, and the technology is developed on the basis of accurate modeling of the sea clutter and the target. Sea clutter is the vector sum of sea surface backscatter signals, and low resolution sea clutter can be modeled as a random variable of gaussian distribution; whereas high-resolution sea clutter presents more peaks, the amplitude distribution presents a "heavy tailing" phenomenon, and a composite gaussian model is typically used for modeling such non-gaussian sea clutter. The target signal received by high-resolution radar is typically distributed over a plurality of range bins while also exhibiting an expansion in the doppler dimension, and thus can be modeled as a multi-rank linear subspace range expansion target. On the basis of sea clutter and target modeling, a correlation learner provides a self-adaptive distance expansion target detector based on a two-step generalized likelihood ratio criterion, however, the detector only uses echo information of a single polarization channel, and has poor detection capability on weak targets on the sea surface.
The adaptive distance under the unipolar channel expands the limited polarization information used by the target detector, so the performance is poor when detecting the weak target; the performance of the adaptive matched filtering technology is limited by the number of auxiliary units, and serious performance degradation can occur in a non-uniform sea clutter background with a small number of auxiliary units.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a subspace distance expansion target detection method based on a polarized radar. The technical problems to be solved by the invention are realized by the following technical scheme:
the subspace distance expansion target detection method based on the polarized radar provided by the invention comprises the following steps:
transmitting pulse signals to the sea surface by using a radar transmitter only comprising a single polarized antenna, and receiving sea surface backscattering signals by using a receiver comprising an orthogonal polarized antenna to obtain radar echo data of two polarized channels in a unit to be detected;
Wherein, a plurality of distance units occupied by the target to be detected form a unit to be detected;
converting radar echo data of a unit to be detected by using a unitary matrix;
L distance units are selected around the unit to be detected to serve as reference units, and data of two polarization channels in the reference units are used as auxiliary data;
according to the auxiliary data of the two polarization channels, respectively and iteratively calculating sea clutter speckle covariance matrix estimation values corresponding to the two polarization channels;
Respectively converting sea clutter speckle covariance matrix estimated values of two polarized channels by using unitary matrixes, and jointly writing the converted estimated values into a polarized speckle covariance matrix form;
Calculating the test statistic of the unit to be detected according to the sea wave speckle covariance matrix in the form of the polarization speckle covariance matrix;
Indexing a decision threshold according to the number of units to be tested, the accumulated pulse number, the false alarm rate and the reference unit number;
and comparing the test statistic with the indexed judgment threshold to determine whether the sea level has the target.
Optionally, converting radar echo data of the two polarized channels using a unitary matrix includes:
Selecting a form of unitary matrix according to the number of pulses in the coherent processing interval;
And converting radar echo data of the unit to be detected according to the selected unitary matrix form to obtain converted radar echo data.
The radar echo data of two polarized channels in the unit to be detected are respectively expressed as follows:
x HH,i＝[xHH,i(1),xHH,i(2),...,xHH,i(N)]T and x HV,i＝[xHV,i(1),xHV,i(2),...,xHV,i(N)]T,
Where i=1, 2,..h, N is the number of pulses in one coherent processing interval, [ · ] T is the matrix transpose.
Wherein the form of the selected unitary matrix is expressed as:
Wherein I N/2 and I (N-1)/2 are N/2 and (N-1)/2 order unit arrays, respectively, and Q is in the form of
The converted radar echo data is expressed as:
Optionally, respectively iteratively calculating the sea clutter speckle covariance matrix estimation values corresponding to the two polarization channels according to the auxiliary data of the two polarization channels includes:
respectively inputting auxiliary data of the two polarized channels into corresponding estimation equations, setting iteration initial values of the estimation equations, and carrying out iteration multiple times to obtain sea clutter speckle covariance matrix estimation values corresponding to the two polarized channels;
wherein, the estimation equation corresponding to the two polarization channels is expressed as:
the initial iteration value is expressed as:
Where m represents the number of iterations.
Wherein, the sea wave speckle covariance matrix in the form of a polarization speckle covariance matrix is expressed as:
wherein Re (. Cndot.) represents the real part taking operation.
Wherein the test statistic is expressed as:
in 2x 2 dimensional matrix The dimension N i is determined using the MDL criteria,The Doppler frequency is estimated by an ESPRIT spectrum estimation method;
optionally, indexing the detection threshold according to the number of units to be detected, the number of accumulated pulses, the false alarm rate and the number of reference units includes:
according to different numbers of units to be detected, accumulated pulse numbers, false alarm rates and reference unit numbers, performing multiple independent Monte Carlo tests to obtain corresponding decision threshold values;
and establishing indexes of a decision threshold and the number of units to be tested, the accumulated pulse number, the false alarm rate and the reference unit number.
Optionally, comparing the test statistic with the indexed decision threshold, and determining whether the sea level has the target comprises:
comparing the detection statistic with the indexed judgment threshold, and determining that a target exists on the sea surface when the detection statistic is not smaller than the indexed judgment threshold;
And when the detection statistic is smaller than the indexed judgment threshold, determining that the sea surface does not have a target.
Advantageous effects
According to the subspace distance extended target detection method based on the polarized radar, provided by the invention, the target detection is carried out by combining echo data of two polarized channels, and the detection performance is improved by using different polarization characteristics of sea clutter and targets; meanwhile, the oblique symmetry characteristic of the sea clutter is added into target detection, and echo data is converted by using a unitary matrix, so that dependence on the number of auxiliary units is reduced by using priori information of the clutter covariance matrix, and the detection performance under the heterogeneous sea clutter background is improved.
Drawings
FIG. 1 is a schematic process diagram of a subspace distance expansion target detection method based on a polarized radar;
FIG. 2 is a schematic diagram showing the influence of the number of auxiliary units on the detection performance;
FIG. 3 is a schematic diagram showing the effect of inter-polarization-channel sea clutter power ratio on detection performance;
fig. 4 is a schematic diagram showing comparison of measured data detection performance provided by the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but embodiments of the present invention are not limited thereto.
As shown in fig. 1, the method for detecting a subspace distance expansion target based on a polarized radar provided by the invention comprises the following steps:
S1, transmitting pulse signals to the sea surface by using a radar transmitter only comprising a single polarized antenna, and receiving sea surface backscattering signals by using a receiver comprising an orthogonal polarized antenna to obtain radar echo data of two polarized channels in a unit to be detected;
Wherein, a plurality of distance units occupied by the target to be detected form a unit to be detected;
assuming that an object to be detected occupies H distance units, the object to be detected is called a unit to be detected, and radar echo data of two polarized channels in the unit to be detected are respectively expressed as:
x HH,i＝[xHH,i(1),xHH,i(2),...,xHH,i(N)]T and x HV,i＝[xHV,i(1),xHV,i(2),...,xHV,i(N)]T,
Where i=1, 2,..h, N is the number of pulses in one coherent processing interval, [ · ] T is the matrix transpose.
S2, converting radar echo data of a unit to be detected by using a unitary matrix;
The invention needs to select the form of unitary matrix according to the pulse number in the coherent processing interval; and converting radar echo data of the unit to be detected according to the selected unitary matrix form to obtain converted radar echo data.
Wherein the form of the selected unitary matrix is expressed as:
Wherein I N/2 and I (N-1)/2 are N/2 and (N-1)/2 order unit arrays, respectively, and Q is in the form of
The converted radar echo data is expressed as:
S3, selecting L distance units around the unit to be detected as reference units, and taking data of two polarization channels in the reference units as auxiliary data;
and selecting auxiliary data of L distance units around the unit to be detected, wherein k=H+1, H+2, & gt, H+L, and the auxiliary data are used for estimating a sea clutter speckle covariance matrix.
S4, respectively and iteratively calculating sea clutter speckle covariance matrix estimation values corresponding to the two polarization channels according to auxiliary data of the two polarization channels;
The auxiliary data of the two polarized channels can be respectively input into corresponding estimation equations, iteration initial values of the estimation equations are set, and sea clutter speckle covariance matrix estimation values corresponding to the two polarized channels are obtained through iterative computation for many times;
iterative computation of the corresponding speckle covariance matrix using the auxiliary data of HH and HV polarized channels:
wherein, the estimation equation corresponding to the two polarization channels is expressed as:
wherein [ (35 ] H represents conjugate transpose, m represents iteration number, generally 3-5 is taken, and the initial iteration values are respectively
S5, respectively converting the sea clutter speckle covariance matrix estimated values of the two polarized channels by using a unitary matrix, and jointly writing the converted estimated values into a polarized speckle covariance matrix form;
The invention obtains the sea clutter speckle covariance matrix estimation values of two polarized channels AndThen, the unitary matrix in S2 is used for conversion and written into a polarized speckle covariance matrix form:
wherein Re (. Cndot.) represents the real part taking operation.
S6, calculating the test statistic of the unit to be detected according to the sea wave speckle covariance matrix in the form of the polarization speckle covariance matrix;
wherein the test statistic is expressed as:
in 2x 2 dimensional matrix The number of dimensions N i is determined using MDL criteria and, after obtaining an estimate of the number of dimensions,The Doppler frequency is estimated by an ESPRIT spectrum estimation method;
Calculation with MDL criteria The dimension N i of (a) is as follows:
1. calculating covariance matrix of ith unit to be detected on HV polarized channel And performing eigenvalue decomposition, and sorting the eigenvalues from large to small to obtain lambda 1,λ2,...,λN.
2. Substituting the characteristic value into the following formula to obtain the m value minimizing the following formulaIs of dimension N i = m.
MDL(m)＝(N-m)lnΛ(m),m＝0,1,...,N-1；
In the method, in the process of the invention,
Obtained by ESPRIT algorithmThe doppler frequency component f i,1,fi,2 of,
1. Defining a new random process y i, namely y i(n)＝xHV,i (n+1), according to the unit data x HV,i to be detected of the ith distance unit on the HV channel;
2. Calculating cross-correlation matrix Singular value decomposition is carried out on the complex, and the minimum singular value is sigma 2;
3. Two matrices C xx,i＝Rxx,i-σ2I,Cxy,i＝Rxy,i-σ2 Z are defined which,
Wherein,
4. Solving the generalized eigenvalue decomposition of the matrix { C xx,i,Cxy,i }, obtaining the generalized eigenvalue positioned on the unit circle, namely the estimated value f i,1,fi,2 of Doppler frequency,
The steering matrix is:
5. Singular value decomposition is performed on the steering matrix E i to obtain E i＝UiΛiVi, Wherein the method comprises the steps ofRepresenting the kronecker product operation.
S7, indexing a judgment threshold according to the number of units to be tested, the accumulated pulse number, the false alarm rate and the reference unit number;
According to the invention, multiple independent Monte Carlo tests can be carried out according to different numbers of units to be tested, accumulated pulse numbers, false alarm rates and reference unit numbers, so as to obtain corresponding decision threshold values; and establishing indexes of the decision threshold, the number of units to be tested, the accumulated pulse number, the false alarm rate and the reference unit number, so that when the decision is carried out, the corresponding decision threshold can be indexed only according to the current number of units to be tested, the accumulated pulse number, the false alarm rate and the reference unit number.
S8, comparing the test statistic with the indexed judgment threshold to determine whether a target exists at the sea level.
After obtaining the test statistics of the units to be detected, carrying out detection judgment according to the number H of the units to be detected, the accumulated pulse number N, the false alarm rate P fa and the reference unit number L index detection threshold eta, and judging whether a target exists.
Comparing the detection statistic with an indexed judgment threshold, and determining that a target exists on the sea surface when the detection statistic is not smaller than the indexed judgment threshold; and when the detection statistic is smaller than the indexed judgment threshold, determining that the sea surface does not have a target. The following formula is shown:
The decision threshold eta is determined by 100/P fa independent Monte Carlo tests, H1 represents that a target exists, and H0 represents that the target does not exist.
According to the subspace distance extended target detection method based on the polarized radar, provided by the invention, the target detection is carried out by combining echo data of two polarized channels, and the detection performance is improved by using different polarization characteristics of sea clutter and targets; meanwhile, the oblique symmetry characteristic of the sea clutter is added into target detection, and echo data is converted by using a unitary matrix, so that dependence on the number of auxiliary units is reduced by using priori information of the clutter covariance matrix, and the detection performance under the heterogeneous sea clutter background is improved.
The outstanding performance of the present invention compared to conventional detectors is described in connection with the experiments below.
Referring to fig. 2, fig. 2 is a schematic diagram showing the influence of the number of auxiliary units on the detection performance. In fig. 2, the horizontal axis represents the signal-to-noise ratio, and the vertical axis represents the detection probability. Test 1 uses sea clutter simulation data of a composite gaussian model to evaluate the performance of the detector and compares the performance of the detectors of different auxiliary units. As can be seen from fig. 2, the detection probability of the present invention is higher than that of the conventional detector under different auxiliary units.
Referring to fig. 3, fig. 3 is a schematic diagram illustrating the effect of the inter-polarization-channel sea clutter power ratio on the detection performance. In fig. 3, the horizontal axis represents the signal-to-noise ratio, and the vertical axis represents the detection probability. And 2, evaluating the performance of the detector by using sea clutter simulation data of a composite Gaussian model, and comparing the performances of the detector when the sea clutter power between polarized channels is different. As can be seen from fig. 3, in the case of the difference in sea clutter power between the contrast polarization channels, the detection probability of the present invention is higher than that of the conventional detector.
Referring to fig. 4, fig. 4 is a schematic diagram showing comparison of measured data detection performance. In fig. 4, the horizontal axis represents the signal-to-noise ratio, and the vertical axis represents the detection probability. Test 3 sea clutter measured data with a range resolution of 15m number 19980212_195704_antstep observed by the IPIX radar was selected for performance comparison. As can be seen from fig. 4, the detection probability of the present invention is higher than that of the conventional detector.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
The foregoing is a further detailed description of the invention in connection with the preferred embodiments, and it is not intended that the invention be limited to the specific embodiments described. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.
Claims (5)
1. The subspace distance expansion target detection method based on the polarized radar is characterized by comprising the following steps of:
transmitting pulse signals to the sea surface by using a radar transmitter only comprising a single polarized antenna, and receiving sea surface backscattering signals by using a receiver comprising an orthogonal polarized antenna to obtain radar echo data of two polarized channels in a unit to be detected;
Wherein, a plurality of distance units occupied by the target to be detected form a unit to be detected;
converting radar echo data of a unit to be detected by using a unitary matrix;
L distance units are selected around the unit to be detected to serve as reference units, and data of two polarization channels in the reference units are used as auxiliary data;
according to the auxiliary data of the two polarization channels, respectively and iteratively calculating sea clutter speckle covariance matrix estimation values corresponding to the two polarization channels;
Respectively converting sea clutter speckle covariance matrix estimated values of two polarized channels by using unitary matrixes, and jointly writing the converted estimated values into a polarized speckle covariance matrix form;
Calculating the test statistic of the unit to be detected according to the sea wave speckle covariance matrix in the form of the polarization speckle covariance matrix;
Indexing a decision threshold according to the number of units to be tested, the accumulated pulse number, the false alarm rate and the reference unit number;
comparing the test statistic with the indexed judgment threshold to determine whether a target exists at the sea level;
the transforming radar echo data of two polarized channels using a unitary matrix includes:
Selecting a form of unitary matrix according to the number of pulses in the coherent processing interval;
Converting radar echo data of a unit to be detected according to the selected unitary matrix form to obtain converted radar echo data;
Radar echo data of two polarization channels in the unit to be detected are respectively expressed as follows:
x HH,i＝[xHH,i(1),xHH,i(2),...,xHH,i(N)]T and x HV,i＝[xHV,i(1),xHV,i(2),...,xHV,i(N)]T,
Where i=1, 2,..h, N is the number of pulses in one coherent processing interval, [ · ] T is the matrix transpose;
the form of the selected unitary matrix is expressed as:
Wherein I N/2 and I (N-1)/2 are N/2 and (N-1)/2 order unit arrays, respectively, and Q is in the form of
The converted radar echo data is expressed as:
The iterative computation of the sea clutter speckle covariance matrix estimation values corresponding to the two polarization channels respectively according to the auxiliary data of the two polarization channels comprises the following steps:
respectively inputting auxiliary data of the two polarized channels into corresponding estimation equations, setting iteration initial values of the estimation equations, and carrying out iteration multiple times to obtain sea clutter speckle covariance matrix estimation values corresponding to the two polarized channels;
wherein, the estimation equation corresponding to the two polarization channels is expressed as:
the initial iteration value is expressed as:
Where m represents the number of iterations.
2. The polarized radar-based subspace distance extended target detection method according to claim 1, wherein the sea-clutter speckle covariance matrix in the form of a polarized speckle covariance matrix is expressed as:
wherein Re (. Cndot.) represents the real part taking operation.
3. The polarized radar-based subspace distance-extended target detection method of claim 2, wherein the test statistic is expressed as:
in 2x 2 dimensional matrix The dimension N i is determined using the MDL criteria,The Doppler frequency is estimated by an ESPRIT spectrum estimation method;
4. The polarized radar-based subspace distance extended target detection method according to claim 1, wherein indexing the detection threshold according to the number of units to be detected, the number of accumulated pulses, the false alarm rate, and the number of reference units comprises:
according to different numbers of units to be detected, accumulated pulse numbers, false alarm rates and reference unit numbers, performing multiple independent Monte Carlo tests to obtain corresponding decision threshold values;
and establishing indexes of a decision threshold and the number of units to be tested, the accumulated pulse number, the false alarm rate and the reference unit number.
5. The polarized radar-based subspace distance extended target detection method of claim 1, wherein comparing the test statistic to the indexed decision threshold, determining whether a target is present at sea level comprises:
comparing the detection statistic with the indexed judgment threshold, and determining that a target exists on the sea surface when the detection statistic is not smaller than the indexed judgment threshold;
And when the detection statistic is smaller than the indexed judgment threshold, determining that the sea surface does not have a target.
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