CN113702937A - Double-channel incoherent detection method based on self-adaptive MTI filter - Google Patents

Double-channel incoherent detection method based on self-adaptive MTI filter Download PDF

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CN113702937A
CN113702937A CN202110946365.3A CN202110946365A CN113702937A CN 113702937 A CN113702937 A CN 113702937A CN 202110946365 A CN202110946365 A CN 202110946365A CN 113702937 A CN113702937 A CN 113702937A
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CN113702937B (en
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水鹏朗
孙卓
许述文
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Xidian University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/08—Systems for measuring distance only
    • G01S13/10—Systems for measuring distance only using transmission of interrupted, pulse modulated waves
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The invention discloses a double-channel incoherent detection method based on a self-adaptive MTI filter. The implementation scheme is as follows: receiving an echo data matrix by using a radar; recombining the echo data matrix along a pulse dimension and carrying out block processing along a distance dimension by referring to the accumulated pulse number; determining a distance unit to be detected in the processed echo data and estimating a covariance matrix of the distance unit to be detected; designing a self-adaptive MTI filter by utilizing the covariance matrix estimation value; designing two detection channels by using the obtained filter and respectively calculating to obtain the test statistic of the distance unit to be detected of each channel; comparing the test statistics of the two channels and obtaining the maximum test statistics; according to the detection steps, calculating a judgment threshold by a Monte Carlo method; and judging the distance unit where the maximum detection statistic larger than the threshold is positioned as a target, otherwise, judging the distance unit as no target. The method can effectively inhibit sea clutter and improve the detection effect, and can be used for detecting the target of the sea radar under the background of the sea clutter.

Description

Double-channel incoherent detection method based on self-adaptive MTI filter
Technical Field
The invention belongs to the technical field of target detection, and particularly relates to a two-channel incoherent detection method which can be used for detecting targets of a sea radar under a sea clutter background.
Background
Effective target detection in the background of sea clutter is one of important tasks of shore-based and ship-based radar for sea monitoring. The main difficulty of detection is the complex nature of the sea clutter itself and the low signal-to-clutter ratio characteristic of the target echo. The sea clutter is related to natural factors such as sea conditions, climatic environment, wind speed and wind direction, and a plurality of factors such as radar frequency, polarization mode, resolution ratio and ground wiping angle, and shows complex characteristics such as non-stationary in time, non-uniform in space and non-Gaussian in statistical characteristics. These complex characteristics require that the detection method must use adaptive processing to estimate the statistical properties of the sea clutter in real time and to eliminate as much as possible the effect of the clutter on target detection. Meanwhile, for weak moving targets, simple self-adaptive detection is often difficult to effectively detect the targets, and incoherent accumulation is carried out on the targets, so that the signal-to-noise ratio of target echoes can be improved, and the targets can be quickly detected.
In the traditional incoherent detection method, data is only processed by incoherent accumulation, so that the signal-to-noise ratio of a target is improved, but clutter is not inhibited. The literature' time-of-flight, Roc-Long, ANMF and CM-CFAR performance analysis under K distribution sea clutter [ J ]. university of northwest (Nature science edition), 2012,42(3): 359-. However, the method does not suppress the clutter, and the influence of the clutter still exists, so that the detection effect is not ideal.
Plum-east-chen, water peng, schanzhu, scientific university of west' an university of electronic technology, science edition 2016,43(6):21-26.doi:10.3969/j.issn.1001-2400.2016.06.004 proposes a block whitening clutter suppression method for detecting small floating targets on the sea surface, which is to perform block whitening processing on sea clutter before detection so as to effectively suppress the influence of static clutter such as ground clutter. However, most of the common sea clutter is motion clutter, and the block whitening processing method cannot well suppress the motion clutter, so that the method has a poor effect when processing echo data containing the motion clutter.
Disclosure of Invention
The invention aims to provide a double-channel incoherent detection method based on an adaptive MTI filter aiming at the defects of the prior art so as to effectively inhibit motion clutter and improve the detection effect.
In order to achieve the purpose, the technical scheme of the invention comprises the following steps:
(1) transmitting continuous pulse signals by using a radar, irradiating the pulse signals to the surface of an object to generate echoes, and receiving an echo data matrix X with the size of K multiplied by Q by using the radar, wherein K represents the number of distance units of the echo data received by the radar, namely the distance dimension, and Q represents the pulse number of the signals received by the radar, namely the pulse dimension;
(2) the echo data matrix X is divided again along the pulse dimension, namely the echo data matrix X is divided into B echo data blocks from left to right according to the accumulated pulse number N and every N columns, and the obtained echo data are recombined into a three-dimensional matrix D with the size of NxKxB;
(3) and partitioning the recombined echo data D along a distance dimension, wherein each R distance units form a distance block, R is a positive integer and belongs to [2, K ], and if the number of the last remaining distance units is less than R, the last remaining distance units form a distance block.
(4) Determining the b-th range cell of the w-th cumulative pulse in the recombined echo data D as the range cell z to be detectedb,wThe range unit belongs to the q-th range block D of the echo data DqSelecting a distance block DqAll distance cells of the w-th accumulated pulse of (2) as reference cells, and a distance block DqIs denoted as P, the q-th distance block D is calculatedqOf the w-th accumulated pulse
Figure BDA0003216688600000021
Wherein w is 1,2, …, beta and b is 1,2, …, K; p is a natural number more than or equal to 1;
(5) according to the covariance matrix
Figure BDA0003216688600000022
Designing r-order adaptive moving target detection MTI filter, wherein r is a positive integer and belongs to [3, N-2 ]]Distance unit z to be detectedb,wBy filter processingObtaining a filtered distance unit z 'to be detected'b,wAnd the q-th distance block D after filteringqOf the w-th accumulated pulse
Figure BDA0003216688600000023
(6) Designing two channels, the first channel being based on the unit of the detected distance zb,wSum covariance matrix
Figure BDA0003216688600000024
Calculating a test statistic ζ of the b-th distance unit of the w-th accumulation pulse in the echo data D1,b,w(ii) a The second channel is provided with a unit z 'according to the filtered distance to be detected'b,wSum covariance matrix
Figure BDA0003216688600000025
Calculating the test statistic Zeta of the b-th distance unit of the w-th accumulated pulse in the echo data D after filtering2,b,w；
(7) Two test statistics ζ obtained from two channels1,b,wAnd ζ2,b,wComparing, and taking the larger test statistic as the maximum test statistic ζ of the b-th distance unit of the w-th accumulated pulse in the echo data Db,w；
(8) Traversing the echo data D in the processes from (4) to (7) to obtain K multiplied by B maximum test statistics, arranging the maximum test statistics in a descending order, and taking the [ K multiplied by B multiplied by f ] of the K multiplied by B maximum test statistics after the descending order]The value is used as the detection threshold TζWherein [ KxB × f]Representing the maximum integer not exceeding the real number K multiplied by B multiplied by f, wherein f represents the set false alarm probability, and f belongs to (0, 1);
(9) will maximize test statistic ζb,wAnd a detection threshold TζAnd comparing to judge whether the target exists:
if ζb,w≥TζThen the target exists at the b-th range gate of the w-th accumulated pulse of the echo data,
otherwise, the b-th range gate of the w-th accumulated pulse of the echo data has no target.
Compared with the prior art, the invention has the following advantages:
1) according to the invention, the echo data is subjected to blocking processing along the distance dimension, and the distance block where the unit to be detected is located is used as the reference unit, so that only the covariance matrix of the distance block needs to be calculated when the covariance matrix is calculated, and the subsequent operation amount is greatly reduced;
2) the invention uses the self-adaptive MTI filter to filter the processed echo data, thereby inhibiting the motion clutter in the background clutter and effectively improving the signal-to-clutter ratio and the detection performance of the target.
3) According to the invention, because two channels are constructed, the first channel uses data before filtering for detection, the second channel uses the filtered data for detection, and the two channels can be simultaneously detected and complemented, so that the problem that the adaptive MTI filter filters the moving clutter and simultaneously filters the target when the Doppler shift of the moving target is close to that of the moving clutter is solved, and the detection performance is improved.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
fig. 2 is a diagram of a detection result of detecting measured data by using a conventional incoherent detection method in a simulation experiment.
Fig. 3 is a diagram of a detection result of detecting measured data by using a conventional non-coherent detection method after adaptive MTI filtering in a simulation experiment.
FIG. 4 is a diagram of the results of testing measured data using the present invention in a simulation experiment.
Detailed Description
The embodiments and effects of the present invention will be further explained with reference to the accompanying drawings:
referring to fig. 1, the two-channel incoherent detection method based on the adaptive MTI filter of the present invention includes the following steps:
step 1, echo data are obtained.
Transmitting continuous pulse signals by using a radar, irradiating the pulse signals to the surface of an object to generate echoes, and receiving an echo data matrix X with the size of K multiplied by Q by using the radar, wherein K represents the number of distance units of the echo data received by the radar, namely the distance dimension, and Q represents the pulse number of the signals received by the radar, namely the pulse dimension;
in the embodiment of the present invention, the representation form of the element X (b, q) in the bth row and the qth column of the echo data matrix X is as follows:
Figure BDA0003216688600000041
wherein H0Representing the case where there are only clutter and noise and no targets, H1Representing the presence of clutter and noise and the presence of a target; w (b, q) represents the clutter plus noise signal of the q-th range bin of the kth pulse of the radar, and s (k, q) represents the target signal of the q-th range bin of the kth pulse of the radar.
And 2, sorting the echo data according to the accumulated pulse number.
The echo data matrix X is divided again along the pulse dimension, namely the echo data matrix X is divided into B echo data blocks from left to right according to the accumulated pulse number N, wherein N is more than or equal to 5;
the echo data are recombined into a three-dimensional matrix D of size nxkxb, in this embodiment, the pulse accumulation number N is 6.
And 3, carrying out blocking processing on the distance dimension of the echo data.
And partitioning the recombined echo data D along a distance dimension, wherein each R distance units form a distance block, R is a positive integer and belongs to [2, K ], and if the number of the last remaining distance units is less than R, the last remaining distance units form a distance block.
Step 4, determining a distance unit z to be detectedb,wAnd its reference unit, and estimates covariance matrix
Figure BDA0003216688600000042
Determining the b-th range cell of the w-th cumulative pulse in the recombined echo data D as the range cell z to be detectedb,wThe range unit belongs to the q-th range block D of the echo data DqSelecting a distance block DqAll distance cells of the w-th accumulated pulse of (2) as reference cells, and a distance block DqIs denoted as P, the q-th distance block D is calculatedqOf the w-th accumulated pulse
Figure BDA0003216688600000043
Figure BDA0003216688600000044
Wherein the superscript H denotes taking the conjugate transpose of the matrix, za,q,wThe a-th range bin echo data indicating the q-th range block of the w-th cumulative pulse in the echo data D, w being 1,2, …, beta and b being 1,2, …, K, P being a natural number of 1 or more in this example.
Step 5, designing a self-adaptive MTI filter and calculating a covariance matrix after filtering
Figure BDA0003216688600000051
According to the covariance matrix
Figure BDA0003216688600000052
Designing r-order adaptive moving target detection MTI filter, wherein r is a positive integer and belongs to [3, N-2 ]]In this example, let r be 3, and distance unit z to be detectedb,wProcessing the obtained object by a filter to obtain a filtered distance unit z 'to be detected'b,wAnd the q-th distance block D after filteringqOf the w-th accumulated pulse
Figure BDA0003216688600000058
z′b,w＝Uzb,w
Figure BDA0003216688600000053
The superscript H represents the conjugate transpose of the matrix, and the form of the transfer matrix U is as follows:
Figure BDA0003216688600000054
in the formula, the scalars α, β, and γ are respectively three elements of the eigenvector corresponding to the minimum eigenvalue of the intermediate matrix a, which is expressed as follows:
Figure BDA0003216688600000055
where n is the intermediate variable in the summation symbol.
And 6, designing two channels, and respectively calculating the test statistics of the two channels.
Two channels were designed to compute test statistics in parallel, where:
the first channel is according to the detection distance unit zb,wSum covariance matrix
Figure BDA0003216688600000056
Calculating a test statistic ζ of the b-th distance unit of the w-th accumulation pulse in the echo data D1,b,w：
Figure BDA0003216688600000057
Wherein mean (-) means taking the median of the array in parentheses,
g1,b,wis the intermediate variable of the b-th distance cell of the w-th accumulated pulse in the first channel, expressed as:
Figure BDA0003216688600000061
the superscript H represents the conjugate transpose of the matrix;
g1,R×(q-1)+1,wis an intermediate variable of the R x (q-1) +1 distance unit of the w-th accumulated pulse in the first channel, and representsComprises the following steps:
Figure BDA0003216688600000062
g1,R×(q-1)+2,wis an intermediate variable for the R x (q-1) +2 distance cells for the w-th accumulated pulse in the first channel, expressed as:
Figure BDA0003216688600000063
g1,R×(q-1)+P,wis an intermediate variable of the R x (q-1) + P distance elements of the w-th accumulated pulse in the first channel, expressed as:
Figure BDA0003216688600000064
the second channel is provided with a unit z 'according to the filtered distance to be detected'b,wSum covariance matrix
Figure BDA0003216688600000065
Calculating the test statistic Zeta of the b-th distance unit of the w-th accumulated pulse in the echo data D after filtering2,b,w：
Figure BDA0003216688600000066
Wherein mean (-) means taking the median of the array in parentheses,
g2,b,wis the intermediate variable of the b-th distance cell of the w-th accumulated pulse in the second channel, expressed as:
Figure BDA0003216688600000067
g2,R×(q-1)+1,wis an intermediate variable of the R x (q-1) +1 distance cell of the w-th accumulation pulse in the second channel, expressed as:
Figure BDA0003216688600000068
g2,R×(q-1)+2,wis the w-th channel in the second channelThe mean variable of the R x (q-1) +2 range bins of the product pulse is expressed as:
Figure BDA0003216688600000069
g2,R×(q-1)+P,wis an intermediate variable of the R x (q-1) + P distance elements of the w-th accumulation pulse in the second channel, expressed as:
Figure BDA00032166886000000610
and 7, comparing the test statistics of the two channels to obtain the maximum test statistic.
Two test statistics ζ obtained from two channels1,b,wAnd ζ2,b,wComparing, and taking the larger test statistic as the maximum test statistic ζ of the b-th distance unit of the w-th accumulated pulse in the echo data Db,w。
And 8, determining a detection threshold.
Traversing the echo data D in the processes from the step 4 to the step 7 to obtain K multiplied by B maximum test statistics, arranging the maximum test statistics in a descending order, and taking the [ K multiplied by B multiplied by f ] of the K multiplied by B maximum test statistics after the descending order]The value is used as the detection threshold TζWherein [ KxB × f]Representing the maximum integer not exceeding the real number K multiplied by B multiplied by f, wherein f represents the set false alarm probability, and f belongs to (0, 1);
and 9, judging the target.
Will maximize test statistic ζb,wAnd a detection threshold TζAnd comparing to judge whether the target exists:
if ζb,w≥TζThen the target exists at the b-th range gate of the w-th accumulated pulse of the echo data,
otherwise, the b-th range gate of the w-th accumulated pulse of the echo data has no target.
The effect of this example can be further illustrated by the following simulation:
1. experimental data
Actually measured sea clutter data received by an X-band radar is used in a simulation experiment, the radar working mode is a scanning mode, the pulse repetition frequency is 1000Hz, and the range resolution is 3 m.
The data comprises 1000 distance units and 437 pulse dimension data, the accumulated pulse number is 6, and for the convenience of detection, the echo data is subjected to down 1000 sampling along the pulse dimension. The moving target is unmanned, and the moving mode is that the moving target is firstly far away from the radar and then approaches the radar.
Echo data having undergone pulse accumulation processing in a three-dimensional matrix of 6 × 1000 × 437 is used. And (3) partitioning along the distance dimension, forming a distance block by every 400 distance units, partitioning echo data into 3 distance blocks, and taking the false alarm rate to be 0.001.
2, simulation experiment contents
Simulation 1, the echo data are detected by using a traditional incoherent detection method, and the result is shown in fig. 2.
Simulation 2, using the existing incoherent detection method after adaptive MTI filtering to detect the echo data, the result is shown in fig. 3.
Simulation 3, the invention is used for detecting the echo data, and the result is shown in fig. 4.
In the above-described figure, the horizontal axis represents accumulation time in units of s, the vertical axis represents distance units, and black pixels represent detected objects. The discontinuous tracks in the figure are detected target tracks,
3. analysis of simulation results
As can be seen from fig. 2, the detection probability under this experimental condition by the conventional incoherent detection method is 0.77.
As can be seen from fig. 3, the detection probability of the incoherent detection method after the adaptive MTI filtering under this experimental condition is 0.85.
As can be seen from fig. 4, the detection probability using the present invention under this experimental condition was 0.9.
The two comparison methods are combined with the detection probability comparison of the invention and the target track curve connectivity comparison of the area A and the area B, the detection probability of the invention is higher than that of the two comparison methods, the target track curve connectivity detected at the area A and the area B of the invention is better than that of the two comparison methods, and the stated target detection performance is better than that of the two comparison methods.
The above is only a specific example of the present invention, and does not constitute any limitation to the present invention, and it is obvious that those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention, and those modifications and modifications based on the present invention are within the protection scope of the present invention.

Claims (5)

1. A two-channel incoherent detection method based on an adaptive MTI filter is characterized by comprising the following steps:
(1) transmitting continuous pulse signals by using a radar, irradiating the pulse signals to the surface of an object to generate echoes, and receiving an echo data matrix X with the size of K multiplied by Q by using the radar, wherein K represents the number of distance units of the echo data received by the radar, namely the distance dimension, and Q represents the pulse number of the signals received by the radar, namely the pulse dimension;
(2) the echo data matrix X is divided again along the pulse dimension, namely the echo data matrix X is divided into B echo data blocks from left to right according to the accumulated pulse number N and every N columns, and the obtained echo data are recombined into a three-dimensional matrix D with the size of NxKxB;
(3) and partitioning the recombined echo data D along a distance dimension, wherein each R distance units form a distance block, R is a positive integer and belongs to [2, K ], and if the number of the last remaining distance units is less than R, the last remaining distance units form a distance block.
(4) Determining the b-th range cell of the w-th cumulative pulse in the recombined echo data D as the range cell z to be detectedb,wThe range unit belongs to the q-th range block D of the echo data DqSelecting a distance block DqAll distance cells of the w-th accumulated pulse of (2) as reference cells, and a distance block DqIs denoted as P, the q-th distance block D is calculatedqOf the w-th accumulated pulse
Figure FDA0003216688590000011
Wherein w 1, 2., beta and b 1, 2., K; p is a natural number more than or equal to 1;
(5) according to the covariance matrix
Figure FDA0003216688590000012
Designing r-order adaptive moving target detection MTI filter, wherein r is a positive integer and belongs to [3, N-2 ]]Distance unit z to be detectedb,wProcessing the obtained object by a filter to obtain a filtered distance unit z 'to be detected'b,wAnd the q-th distance block D after filteringqOf the w-th accumulated pulse
Figure FDA0003216688590000013
(6) Designing two channels, the first channel being based on the unit of the detected distance zb,wSum covariance matrix
Figure FDA0003216688590000014
Calculating a test statistic ζ of the b-th distance unit of the w-th accumulation pulse in the echo data D1,b,w(ii) a The second channel is provided with a unit z 'according to the filtered distance to be detected'b,wSum covariance matrix
Figure FDA0003216688590000015
Calculating the test statistic Zeta of the b-th distance unit of the w-th accumulated pulse in the echo data D after filtering2,b,w；
(7) Two test statistics ζ obtained from two channels1,b,wAnd ζ2,b,wComparing, and taking the larger test statistic as the maximum test statistic ζ of the b-th distance unit of the w-th accumulated pulse in the echo data Db,w；
(8) Traversing the echo data D in the processes from (4) to (7) to obtain K multiplied by B maximum test statistics, arranging the maximum test statistics in a descending order, and taking the [ K multiplied by B multiplied by f ] of the K multiplied by B maximum test statistics after the descending order]The value is used as the detection threshold TζWherein [ KxB × f]Representing the largest integer not exceeding the real number K x B x f, f representingSetting false alarm probability, f belongs to (0, 1);
(9) will maximize test statistic ζb,wAnd a detection threshold TζAnd comparing to judge whether the target exists:
if ζb,w≥TζThen the b-th range gate of the w-th cumulative pulse of the echo data has a target, otherwise the b-th range gate of the w-th cumulative pulse of the echo data has no target.
2. The method of claim 1, wherein the qth distance block D is calculated in (4)qOf the w-th accumulated pulse
Figure FDA0003216688590000021
The formula is as follows:
Figure FDA0003216688590000022
wherein the superscript H denotes taking the conjugate transpose of the matrix, za,q,wThe a-th range bin echo data of the q-th range block representing the w-th accumulated pulse in the echo data D.
3. The method of claim 1, wherein the distance element z to be detected in (5)b,wProcessing the obtained object by a filter to obtain a filtered distance unit z 'to be detected'b,wAnd the q-th distance block D after filteringqOf the w-th accumulated pulse
Figure FDA0003216688590000023
Is represented as follows:
z′b,w＝Uzb,w
Figure FDA0003216688590000024
the superscript H represents the conjugate transpose of the matrix, and the form of the transfer matrix U is as follows:
Figure FDA0003216688590000025
the scalars α, β, and γ are respectively three elements of the eigenvector corresponding to the minimum eigenvalue of the intermediate matrix a, and the intermediate matrix a is represented as follows:
Figure FDA0003216688590000026
where n is the intermediate variable in the summation symbol.
4. The method of claim 1, wherein the first channel in (6) is based on a detected distance unit zb,wSum covariance matrix
Figure FDA0003216688590000031
Calculating a test statistic ζ of the b-th range cell of the w-th accumulation pulse in the echo data D1,b,wThe formula is as follows:
Figure FDA0003216688590000032
where mean (-) means taking the median of the array in parentheses, g1,b,wIs the intermediate variable of the b-th distance cell of the w-th accumulated pulse in the first channel, expressed as:
Figure FDA0003216688590000033
the superscript H represents the conjugate transpose of the matrix; g1,R×(q-1)+1,wIs an intermediate variable of the R x (q-1) +1 distance cell of the w-th accumulated pulse in the first channel, expressed as:
Figure FDA0003216688590000034
g1,R×(q-1)+2,wis an intermediate variable for the R x (q-1) +2 distance cells for the w-th accumulated pulse in the first channel, expressed as:
Figure FDA0003216688590000035
g1,R×(q-1)+P,wis an intermediate variable of the R x (q-1) + P distance elements of the w-th accumulated pulse in the first channel, expressed as:
Figure 1
。
5. the method according to claim 1, wherein the second channel in (6) is according to filtered distance units z 'to be detected'b,wSum covariance matrix
Figure FDA0003216688590000037
Calculating the test statistic Zeta of the b-th distance unit of the w-th accumulated pulse in the echo data D after filtering2,b,wThe formula is as follows:
Figure FDA0003216688590000038
where mean (-) means taking the median of the array in parentheses, g2,b,wIs the intermediate variable of the b-th distance cell of the w-th accumulated pulse in the second channel, expressed as:
Figure FDA0003216688590000039
the superscript H represents the conjugate transpose of the matrix; g2,R×(q-1)+1,wIs an intermediate variable of the R x (q-1) +1 distance cell of the w-th accumulation pulse in the second channel, expressed as:
Figure FDA00032166885900000310
g2,R×(q-1)+2,wis an intermediate variable for the R x (q-1) +2 distance cells for the w-th accumulated pulse in the second channel, expressed as:
Figure FDA0003216688590000041
g2,R×(q-1)+P,wis an intermediate variable of the R x (q-1) + P distance elements of the w-th accumulation pulse in the second channel, expressed as:
Figure FDA0003216688590000042
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