CN108387879A - Value detection method in clutter map unit based on adaptive normalization matched filtering - Google Patents
Value detection method in clutter map unit based on adaptive normalization matched filtering Download PDFInfo
- Publication number
- CN108387879A CN108387879A CN201810033473.XA CN201810033473A CN108387879A CN 108387879 A CN108387879 A CN 108387879A CN 201810033473 A CN201810033473 A CN 201810033473A CN 108387879 A CN108387879 A CN 108387879A
- Authority
- CN
- China
- Prior art keywords
- data
- unit
- carried out
- clutter
- resolution cell
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
Abstract
The invention discloses value detection methods in the clutter map unit based on adaptive normalization matched filtering, mainly solve the problems, such as that prior art detection performance is poor, technical solution is：Emit pulse signal using radar transmitter, radar receiver receives echo data, and the echo sequence in each resolution cell of echo data is Z；Test statistics ξ is calculated using adaptive normalized matched filter to Z；Unit intermediate value, which is carried out, using ξ handles to obtain treated dataIt is rightClutter map update is carried out to handle to obtain scanning estimated valueUtilize Monte Carlo Experiment estimation clutter map threshold factor T；Calculate test statistics ξ and scanning estimated valueRatio C, and ratio C and threshold factor T are relatively detected, the result after being detected.The present invention improves the performance of target detection under sea clutter background, improves the robustness of anti-abnormal data, the sea-surface target detection that can be used under movement or static coherent system platform.
Description
Technical field
The invention belongs to signal processing technology fields, and in particular to value detection method in a kind of clutter map unit can be used for
Target detection under movement or static coherent system platform.
Background technology
Target detection technique under sea clutter background is a vital research direction in radar application technology, in army
Thing and civil field have been used widely.When radar under to extra large pattern when working, scanning scene is complicated and range compared with
Greatly, various types of clutters, including sea clutter, land clutter, islands and reefs clutter, coastal waters clutter etc. are usually contained in radar return.
Land clutter and islands and reefs clutter echo strength are stronger, drastically influence the target detection under sea clutter background, complicated clutter scene
The major obstacle of sea-surface target detection is constituted with noise performance.Since noise intensity is influenced by factors such as sea situations, particularly,
It is very violent in spatial domain up conversion in greater coasting area sea clutter intensity, it can only be adopted according to traditional spatial domain class CFAR processing methods
With seldom reference unit, thus false alarm rate loss is very big, and false alarm rate is not easy to keep constant.Although clutter under normal circumstances
Variation on distance and bearing is very violent, but the noise intensity of same range cell change with time be it is slow, because
And time domain constant false alarm processing method may be used, that is, so-called clutter map CFAR methods.
Document " Nitzberg R.Clutter map CFAR analysis [J] .IEEE Transactions on
Aerospace and Electronic systems,1986(4):419-421. " proposes and analyzes first this method, this
The relative smoothness of Radar Clutter Background time domain is utilized in one processing procedure.Radar space is divided into clutter map unit by this method
It works, the intensity that it forms clutter background at detection unit according to detection unit Multiple-Scan value is estimated.Clutter map stores
The amplitude of each azimuth-range unit noise intensity, each value is by new and former scan measures several times iteration
To update, and estimate using it as the intensity of current clutter background.It is single that resolution is only utilized in this method that Nitzberg is proposed
The time-domain information of member, document " Shen Fumin, Liu Zheng clutter map CFAR Plane Detecting Techniques [J] system engineerings and electronic technology,
1996,18(7)：9-14. ", which is proposed, a kind of is suitble to the clutter map unit that is handled sea clutter to be averaged CFAR plane skills
Art is iterated processing again after first carrying out cell-average to each resolution cell amplitude in clutter map unit.This method will be empty
Domain is handled and Time Domain Processing is combined together, and the information for closing on resolution cell is utilized, detection performance is proposed compared with Nitzberg
Method have certain promotion, still, detection performance is not still fine, and this method when there is abnormal point in echo data
Detection property performance can be affected, anti-abnormal data poor performance.
Invention content
It is a kind of based on adaptive normalization matching filter it is an object of the invention in view of the above shortcomings of the prior art, propose
Value detection method in the clutter map unit of wave, to improve anti-abnormal data performance and to the detection performance of target.
To realize the above-mentioned technical purpose, technical scheme of the present invention includes：
(1) it utilizes radar transmitter to emit pulse signal, is received using radar receiver and returned by what surface scattering was formed
Wave number evidence, the echo data are a four-matrix for including the scanning number of turns, pulse dimension, being tieed up apart from peacekeeping wave position, each orientation-
Minimal processing unit apart from two dimensional surface is known as resolution cell, and the echo sequence in each resolution cell is Z：
Z=[z1,z2,...,zi,...,zN],
Wherein ziIndicate that i-th of echo data, N indicate umber of pulse；
(2) adaptive normalization matched filtering processing is carried out to the echo sequence Z in each resolution cell, obtains each point
Distinguish the test statistics ξ of echo sequence in unitn(k)：
Wherein p indicates normalization steering vector, ξn(k) indicate that n-th scans the test statistics of k-th of resolution cell, n
=1,2 ..., L, L indicate scanning the number of turns, ()HIndicate conjugate transposition operation, ()-1It indicates to matrix inversion operation,Table
Show covariance matrix：
Wherein, M indicates reference unit number, zmIndicate reference unit echo data；
(3) to the test statistics ξ of echo sequence in all resolution cellsn(k) it is carried out on azimuth-range two dimensional surface
The processing of unit intermediate value obtains n-th and scans k-th of resolution cell treated dataFromIt is middle to take out (n-1)th time
Scan k-th of resolution cell treated data
(4) to (n-1)th k-th of resolution cell of scanning treated dataClutter map update is carried out, obtains n-th
The estimated value of k-th of resolution cell of secondary scanning
(5) to test statistics ξn(k) self-adapting detecting is carried out：
(5a) estimates clutter map according to the format of data to be tested and the requirement of different false alarm rates, using Monte Carlo Experiment
Threshold factor T；
(5b) calculates test statistics ξn(k) estimated value scanned with n-thRatio C, and by C and thresholding because
Sub- T is compared：
If C >=T, then it is assumed that contain target in the detection unit, i.e., corresponding unit in testing result is set 1；
If C ＜ T, then it is assumed that there is no target in the detection unit, i.e., set to 0 corresponding unit in testing result.
Compared with the prior art, the present invention has the following advantages：
1) present invention is carried on the back due to being handled echo data using adaptive normalization matched filtering in K Distribution Clutters
Detection performance is improved under scape；
2) present invention improves its anti-abnormal number due to being handled the data in detection window using unit median method
According to robustness.
Description of the drawings
Fig. 1 is the implementation flow chart of the present invention；
Fig. 2 is the selection figure of reference unit in estimate covariance matrix of the present invention；
Fig. 3 is the selection figure that invention unit intermediate value handles window；
Fig. 4 is the detection probability comparison diagram obtained using the present invention and existing method.
Specific implementation mode
The invention will be further described below in conjunction with the accompanying drawings：
Referring to Fig.1, steps are as follows for realization of the invention：
Step 1, it is Z to obtain echo sequence.
Emit pulse signal using radar transmitter, the number of echoes formed by surface scattering is received using radar receiver
According to the echo data is a four-matrix for including the scanning number of turns, pulse dimension, being tieed up apart from peacekeeping wave position, each azimuth-range
The minimal processing unit of two dimensional surface is known as resolution cell；
Echo sequence in each resolution cell is Z：
Z=[z1,z2,...,zi,...,zN],
Wherein ziIndicate that i-th of echo data, N indicate umber of pulse.
Step 2, adaptive normalization matched filtering processing is carried out to echo sequence.
The reference unit that (2a) chooses：
With reference to Fig. 2, the embodiment of this step is specific as follows：
(2a1), to avoid target from entering in reference unit, is being detected respectively using each echo sequence z as detection unit
Choose protection location in unit both sides；
(2a2) chooses M resolution cell and be used as altogether in detection unit both sides refers to unit, z in Fig. 21,z2,...,
zm,...,zMAs selected reference unit, wherein zmIndicating the echo sequence of m-th of reference unit, the value of m is 1,
2,...,M；
(2b) is according to the echo sequence z of m-th of reference unitm, using normalization sample covariance matrix NSCM, calculate
To the covariance matrix of detection unit
Wherein, M indicates reference unit number, zmIndicate reference unit echo data, ()HIndicate conjugate transposition operation；
(2c) determines the Doppler frequency shift f of targetd, calculate normalization steering vector p：
Wherein, ()TIndicate transposition operation；
(2d) carries out adaptive normalization matched filtering processing to the echo sequence Z in each resolution cell, obtains each
The test statistics ξ of echo sequence in resolution celln(k)：
Wherein, ξn(k) indicate that the test statistics of k-th of resolution cell n-th scanning, n=1,2 ..., L, L expression are swept
The number of turns is retouched, ()-1It indicates to matrix inversion operation.
Step 3, to test statistics ξn(k) unit intermediate value processing is carried out.
(3a) selection unit intermediate value on azimuth-range two dimensional surface handles window：
With reference to Fig. 3, the embodiment of this step is：With test statistics ξn(k) it is the center of rectangular window, is selected around it
X × Y resolution cell is taken to handle window as unit intermediate value, then in the cells in value processing window with ξn(k) center chooses a × b
Resolution cell is as protection window, remaining resolution cell, which is used as, refers to unit, wherein X indicates window in the length of azimuth dimension, Y tables
Show the length that window is tieed up in distance；A indicates protection window in the length of azimuth dimension, length of the b expressions protection window in distance dimension；This reality
Example setting X is 7, Y 7, a 3, b 3；
The test statistics ξ of (3b) to echo sequence in all resolution cellsn(k) it is carried out at unit intermediate value on window
Reason：
(3b1) is to test statistics ξn(k) the reference unit data in all 7 × 7 square window are pressed respectively from small
It is arranged to big sequence；
It is single that (3b2), which takes data of the intermediate value as 7 × 7 square window center of result after sequence, the data,
First intermediate value treated dataFromIt is middle to take out (n-1)th k-th of resolution cell of scanning treated data
Step 4, clutter map update is handled.
To (n-1)th k-th of resolution cell of scanning treated dataClutter map update is carried out, n-th is obtained
Scan the estimated value of k-th of resolution cell
Wherein, ω is forgetting factor, and value is the constant on [0,1]；Here ω is to examine in order to balance in engineering
Performance and arithmetic speed are surveyed, the value of ω is 0.125,Indicate the estimated value of (n-1)th scanning, k-th of resolution cell.
Step 5, self-adapting detecting processing is carried out to echo sequence.
(5a) requires to carry out to estimate using Monte Carlo Experiment miscellaneous according to the format of data to be tested and different false alarm rates
Wave figure threshold factor T：
(5a1) determines the false alarm rate index needed, counts the length of each dimension of data to be tested；
(5a2) generates corresponding pure clutter data according to the format of false alarm rate index and initial data；
(5a3) handles pure clutter data according to step (2) to step (4), obtains corresponding test statistics ξn
(k) estimated value scanned with n-th
(5a4) calculates initial threshold since threshold factor is unrelated with the position of reference unit, according to self-adapting detecting criterion
Factor Ti, wherein i indicates ith Monte Carlo Experiment, is carried out by following formula：
(5a5) is independently repeated as many times and tests, to the initial threshold factor T obtained every timeiDescending arrangement is carried out, is taken (5a1)
Threshold factor under determining corresponding false alarm rate is as final threshold factor T；
(5b) calculates test statistics ξn(k) estimated value scanned with n-thRatio：And by C and door
Limit factor T is compared：
If C >=T, then it is assumed that contain target in the detection unit, i.e., corresponding unit in testing result is set 1；
If C ＜ T, then it is assumed that there is no target in the detection unit, i.e., set to 0 corresponding unit in testing result.
The clutter map unit median target detection based on adaptive normalization matched filtering is completed based on step 1 to step 5.
The effect of the present invention is described further with reference to emulation experiment.
1. simulation parameter
The data used in emulation experiment are certain motion platform data.
2. emulation experiment content
The method of the present invention and the clutter map inspection based on cell-average is respectively adopted to certain motion platform data in emulation experiment
Survey method carries out target detection, testing result as shown in figure 4, horizontal axis in Fig. 4 indicates that signal to noise ratio, the longitudinal axis indicate detection probability,
Solid line in Fig. 4 indicates the sea-surface target testing result obtained using the present invention；Dotted line in Fig. 4 indicates to use MTD grades of receipts or other documents in duplicates
The testing result that first mean clutter figure detection method obtains；
Figure 4, it is seen that being substantially better than the inspection that existing method obtains using the testing result that the method for the present invention obtains
Survey result.
In conclusion the clutter map unit median target detection proposed by the present invention based on adaptive normalization matched filtering
Method improves the performance that sea-surface target detects under movement or static coherent system platform condition, improves anti-abnormal data
Performance.
Claims (4)
1. value detection method in a kind of clutter map unit based on adaptive normalization matched filtering, which is characterized in that including：
(1) it utilizes radar transmitter to emit pulse signal, the number of echoes formed by surface scattering is received using radar receiver
According to the echo data is a four-matrix for including the scanning number of turns, pulse dimension, being tieed up apart from peacekeeping wave position, each azimuth-range
The minimal processing unit of two dimensional surface is known as resolution cell, and the echo sequence in each resolution cell is Z：
Z=[z1,z2,...,zi,...,zN],
Wherein ziIndicate that i-th of echo data, N indicate umber of pulse；
(2) adaptive normalization matched filtering processing is carried out to the echo sequence Z in each resolution cell, it is single obtains each resolution
The test statistics ξ of echo sequence in membern(k)：
Wherein p indicates normalization steering vector, ξn(k) test statistics of k-th of resolution cell of expression n-th scanning, n=1,
2 ..., L, L indicate the scanning number of turns, ()HIndicate conjugate transposition operation, ()-1It indicates to matrix inversion operation,Indicate association
Variance matrix：
Wherein, M indicates reference unit number, zmIndicate reference unit echo data；
(3) to the test statistics ξ of echo sequence in all resolution cellsn(k) unit is carried out on azimuth-range two dimensional surface
Intermediate value processing obtains n-th and scans k-th of resolution cell treated dataFromIt is middle to take out (n-1)th scanning
K-th of resolution cell treated data
(4) to (n-1)th k-th of resolution cell of scanning treated dataClutter map update is carried out, n-th is obtained and sweeps
Retouch the estimated value of k-th of resolution cell
(5) to test statistics ξn(k) self-adapting detecting is carried out：
(5a) estimates clutter map thresholding according to the format of data to be tested and the requirement of different false alarm rates, using Monte Carlo Experiment
Factor T；
(5b) calculates test statistics ξn(k) estimated value scanned with n-thRatio C, and by C and threshold factor T into
Row compares：
If C >=T, then it is assumed that contain target in the detection unit, i.e., corresponding unit in testing result is set 1；
If C ＜ T, then it is assumed that there is no target in the detection unit, i.e., set to 0 corresponding unit in testing result.
2. the method as described in claim 1, which is characterized in that the inspection of echo sequence in all resolution cells in step (3)
Test statistic ξn(k) unit intermediate value processing is carried out on azimuth-range two dimensional surface, is carried out as follows：
(3a) sets the window that unit intermediate value is handled to 7 × 7 square window, and 3 × 3 guarantor is taken in square window center
Window is protected as protection location, remaining element, which is used as, refers to unit；
(3b) is to test statistics ξn(k) the reference unit data in all 7 × 7 square window are pressed from small to large respectively
It is ranked sequentially；
(3c) takes data of the intermediate value of ranking results as 7 × 7 square window center, which is at unit intermediate value
Data after reason
3. the method as described in claim 1, which is characterized in that scanned at k-th of resolution cell to (n-1)th time in step (4)
Data after reasonClutter map update is carried out, is carried out by following formula：
Wherein, ω is forgetting factor, and value is the constant on [0,1]；Indicate that (n-1)th scanning, k-th of resolution is single
The estimated value of member.
4. the method as described in claim 1, which is characterized in that according to the format of data to be tested and different in step (5)
False alarm rate requires to carry out estimating clutter map threshold factor T using Monte Carlo Experiment, carries out as follows：
(5a) is required according to false alarm rate and data to be tested format generates corresponding pure clutter data；
(5b) handles pure clutter data according to step (2) to step (4), obtains corresponding test statistics ξn(k) with the
The estimated value of n times scanning
(5c) obtains initial threshold factor T since threshold factor is unrelated with reference unit position, according to self-adapting detecting criterioni：
(5d) is independently repeated as many times and tests, to obtained initial threshold factor TiDescending arrangement is carried out, the door under corresponding false alarm rate is taken
The factor is limited as final threshold factor T.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810033473.XA CN108387879B (en) | 2018-01-12 | 2018-01-12 | Clutter map unit median detection method based on adaptive normalized matched filtering |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810033473.XA CN108387879B (en) | 2018-01-12 | 2018-01-12 | Clutter map unit median detection method based on adaptive normalized matched filtering |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108387879A true CN108387879A (en) | 2018-08-10 |
| CN108387879B CN108387879B (en) | 2021-05-18 |
Family
ID=63076305
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810033473.XA Active CN108387879B (en) | 2018-01-12 | 2018-01-12 | Clutter map unit median detection method based on adaptive normalized matched filtering |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108387879B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109856608A (en) * | 2018-11-28 | 2019-06-07 | 重庆秦嵩科技有限公司 | A kind of high confidence rate detection method of radar target based on recurrence clutter map |
| CN110412536A (en) * | 2019-08-15 | 2019-11-05 | 南京信息工程大学 | Object detection method based on mutative scale median ratio |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103954951A (en) * | 2014-05-13 | 2014-07-30 | 西安电子科技大学 | Power mid value and normalization covariance estimation based sea-surface target detection method |
| CN104076350A (en) * | 2014-07-08 | 2014-10-01 | 西安电子科技大学 | Method for detecting floating targets on sea based on normalized Doppler spectrum |
| CN104569949A (en) * | 2015-01-27 | 2015-04-29 | 西安电子科技大学 | Radar target detection method based on combined adaptive normalized matched filter |
| CN104569948A (en) * | 2015-01-21 | 2015-04-29 | 西安电子科技大学 | Sub-band self-adaptive GLRT-LTD detection method under sea clutter background |
-
2018
- 2018-01-12 CN CN201810033473.XA patent/CN108387879B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103954951A (en) * | 2014-05-13 | 2014-07-30 | 西安电子科技大学 | Power mid value and normalization covariance estimation based sea-surface target detection method |
| CN104076350A (en) * | 2014-07-08 | 2014-10-01 | 西安电子科技大学 | Method for detecting floating targets on sea based on normalized Doppler spectrum |
| CN104569948A (en) * | 2015-01-21 | 2015-04-29 | 西安电子科技大学 | Sub-band self-adaptive GLRT-LTD detection method under sea clutter background |
| CN104569949A (en) * | 2015-01-27 | 2015-04-29 | 西安电子科技大学 | Radar target detection method based on combined adaptive normalized matched filter |
Non-Patent Citations (1)
| Title |
|---|
| 刘明 等: "基于功率中值和归一化采样协方差矩阵的自适应匹配滤波检测器", 《电子与信息学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109856608A (en) * | 2018-11-28 | 2019-06-07 | 重庆秦嵩科技有限公司 | A kind of high confidence rate detection method of radar target based on recurrence clutter map |
| CN110412536A (en) * | 2019-08-15 | 2019-11-05 | 南京信息工程大学 | Object detection method based on mutative scale median ratio |
| CN110412536B (en) * | 2019-08-15 | 2022-06-24 | 南京信息工程大学 | Target detection method based on variable-scale median ratio |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108387879B (en) | 2021-05-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Orlando et al. | Track-before-detect strategies for STAP radars | |
| Huang et al. | Radar high speed small target detection based on keystone transform and linear canonical transform | |
| CN104977585B (en) | A kind of motion sonar target detection method of robust | |
| CN107942324B (en) | Multi-frame combined small target dual detection method based on Doppler guidance | |
| CN112731307B (en) | RATM-CFAR detector based on distance-angle joint estimation and detection method | |
| Inggs et al. | Ship target recognition using low resolution radar and neural networks | |
| Xue et al. | Knowledge-based target detection in compound Gaussian clutter with inverse Gaussian texture | |
| CN108196238A (en) | Clutter map detection method based on adaptive matched filter under Gaussian background | |
| Tohidi et al. | Compressed-domain detection and estimation for colocated MIMO radar | |
| CN115390027A (en) | Target knowledge auxiliary intelligent fusion detection method under heterogeneous clutter | |
| CN108387879A (en) | Value detection method in clutter map unit based on adaptive normalization matched filtering | |
| El Mashade | Analysis of adaptive detection of moderately fluctuating radar targets in target multiplicity environments | |
| CN112255608A (en) | Radar clutter self-adaptive suppression method based on orthogonal projection | |
| Willett et al. | Application of the MLPDA to bistatic sonar | |
| CN113093174B (en) | PHD filter radar fluctuation weak multi-target-based pre-detection tracking method | |
| CN114355324A (en) | Flight path generation method | |
| CN108983227B (en) | Polarization MIMO radar detection method based on whitening filtering | |
| Behar et al. | Hough detector with adaptive non-coherent integration for target detection in pulse jamming | |
| Oyedokun | Sea clutter simulation | |
| Wang et al. | Seafloor terrain detection from acoustic images utilizing the fast two-dimensional CMLD-CFAR | |
| Geng et al. | Joint estimation of target state and ionosphere state for OTHR based tracking | |
| Chen et al. | Adaptive detection in compound-Gaussian clutter with partially correlated texture | |
| CN115372913B (en) | Rapid compensation method for target distance walking | |
| Anderson et al. | HF skywave radar: estimating aircraft heights using super-resolution in range | |
| Kabakchiev et al. | Netted radar Hough detector in randomly arriving impulse interference |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |