CN106646382A - Clutter extensive cancellation algorithm based on coefficient expectations - Google Patents
Clutter extensive cancellation algorithm based on coefficient expectations Download PDFInfo
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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
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- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
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Abstract
The invention relates to a clutter extensive cancelation algorithm based on coefficient expectations (ECA-E). The method comprises the following steps: using the same manner as the extensive cancelation batch processing algorithm to segment a clutter matrix and a monitoring signal followed by the delay processing of a reference signal and the constructing of a clutter matrix with the same dimensions; using by each segmented signal the least squares method to estimate the clutter coefficients; based on the clutter coefficients estimated by each segmented signal, seeking the expected clutter coefficient of the entire segment data; and returning the unified clutter coefficient to each segment data for clutter suppression. The method of the invention has an excellent suppressive ability to static clutters. When the ECA-E and the ECA-B algorithms are combined, the static clutters and strongly dynamic clutters are suppressed at the same time; therefore, a better suppression effect can be achieved. In addition, on the basis that the clutter suppression performance is ensured, through the segmented processing algorithm, a better parallel structure can be obtained; and the computing loss of each section can be reduced substantially. The parallel computing obviously raises the computing efficiency so as to further increase the real-time performance of an entire outer radiation source radar system.
Description
Technical field
The present invention relates to external illuminators-based radar field, more particularly to a kind of time domain clutter suppression method.
Background technology
In recent years, by the use of third party's radiation source as the external illuminators-based radar of irradiation source because its environmental protection, good concealment,
Strong antijamming capability, with good anti-stealth capability many advantages, such as be increasingly becoming study hotspot both domestic and external.External radiation
Source radar itself not transmission signal, needs to receive direct-path signal as reference signal for follow-up signal process.Therefore, in thunder
Need up in system comprising two class passages：The reference channel for receiving direct wave and the monitoring passage for receiving target echo.And generally select
Irradiation source works in continuous wave mode, and monitoring passage is inevitably received to go directly and involves multipath signal (hereinafter
In be referred to as multipath clutter), these multipath clutter signals are much stronger than target echo.On the other hand, most of irradiation source is not
For Radar Design, the autoambiguity function of signal has relatively low peak sidelobe ratio.This causes calculating reference signal and prison
When surveying the cross ambiguity function of signal, the peak value of target can be fallen into oblivion by the secondary lobe of multipath clutter, only suppress multipath clutter first
Highlight can target.Therefore, it is one of committed step of external illuminators-based radar signal transacting that multipath clutter suppresses.
There are various Clutter suppression algorithms to be suggested now, time-domain filtering, spatial domain filter can be divided into from suppression principle
Ripple and frequency domain filtering.Time-domain filtering method accounts for master because its rejection ability is strong, relatively low to system requirements in Clutter suppression algorithm
Lead status.In numerous time-domain filtering methods, the clutter extension cancellation algorithm (Extensive derived based on least square
Cancellation Algorithm, ECA) because its rejection ability is strong, be easy to the advantages of restraining, it is widely used in recent years.For
The preferable inhibition of acquisition, algorithm needs to build larger clutter space matrix, increased algorithm amount of calculation, while also right
Hardware memory space is put forward higher requirement.In order to reduce the computing consumption of algorithm, cancellation batch algorithms are extended
(Extensive Cancellation Algorithm Batches, ECA-B) is suggested.ECA-B algorithms are by after signal subsection
Per section is filtered respectively using ECA algorithms, reduces the dimension of clutter subspace and maximum computing storage area consumption.Pass through simultaneously
Segment processing increased wave filter null width, reduce computing integration time, and algorithm has more preferable under non-stationary environment
Robustness.But wave filter null width is determined by the integration time of every segment data, it means that per segment data integration time not
Can be too short, limit the maximum segment number of ECA-B algorithms.Simultaneously algorithm can also cause modulation to low Doppler's target.Sliding window expands
Exhibition cancellation algorithm (Extensive Cancellation Algorithm Sliding, ECA-S) is by increasing extra sliding window
Unit carrys out estimation filter coefficient to improve the problems referred to above.But in order to obtain good rejection, needs newly increase a large amount of
Sliding window unit, greatly improve algorithm overall calculation amount.
With the development of external illuminators-based radar technology, the engineer applied of external illuminators-based radar is being received in recent years increasingly
The concern for coming, and real-time processing is the premise of its engineer applied.Maximum as amount of calculation in external illuminators-based radar signal transacting
One of step, the real time implementation of time domain clutter recognition determines the performance that whole system real time implementation works.It is existing by above-mentioned analysis
Some ECA systems algorithm has respective limitation on real time implementation is realized, limits the performance of Clutter suppression algorithm real time implementation.
The content of the invention
For problem set forth above, it is an object of the invention to provide a kind of extend cancellation side based on the desired clutter of coefficient
Method.
One kind proposed by the invention extends cancellation method (Extensive based on the desired clutter of coefficient
Cancellation Algorithm Expectation, ECA-E), it is characterised in that comprise the steps of：
Step one：By reference signal SrefWith monitoring signals SsurvIt is divided into b sections, i-th section of reference signal and monitoring signals point
It is not：With
Wherein, N is monitoring signals length, R be reference signal it is extra needed for sample number, and R is not less than distance element K that need to suppress；
Step 2：Reference signal after segmentation is pressed into unified rule construct clutter matrix, then i-th section of reference signal Srefi
The clutter matrix of construction is expressed as：Ci=B [Srefi DSrefi D2Srefi…DK-1Srefi].Wherein, B is incidence matrix, for carrying
Take the last of matrixRow element, is defined asD is displacement
Matrix, is defined as
Step 3：Segmentation least-squares estimation clutter matrix coefficient, the i-th segment data clutter matrix coefficient θiIt is estimated as
Step 4：Expectation is asked to every hop count clutter matrix coefficient according to estimates
Step 5：ReturnCarry out after clutter recognition, being in order stitched together per segment data to every segment data, obtain whole
The clutter recognition result of segment data.
Weights when asking parameter to expect in step 4 can further simplify：When reference signal be stationary signal, signal work(
When rate is approximate constant, the energy approximation after homogenous segmentations per segment signal is equal, it is therefore desirable for ask for expression formula can be with abbreviationThe method that taking expression formula after simplifying carries out clutter recognition is referred to as ECA-ES (Simplified ECA-E).
ECA-E and ECA-ES algorithms possess outstanding static clutter suppression capability, and poor to dynamic clutter suppression capability,
In practical application, can with extension cancellation batch algorithms (Extensive Cancellation Algorithm Batches,
ECA-B) combine, while suppressing static clutter and by force dynamic clutter, obtain more preferable clutter recognition effect.This second-order filter scheme
ECA-E＆B and ECA-ES＆B is referred to as, is comprised the steps of：
Step one：Using static clutter recognitions of the ECA-E or ECA-ES to front K distance element, and retain algorithm segmentation knot
Structure；
Step 2：Using ECA-B algorithms to the K near direct waveBIndividual distance element carries out clutter recognition, algorithm segmental structure
It is identical with step one；
Step 3：To in order be stitched together per segment data, obtain the clutter recognition result of whole segment data.
Cancellation method (Extensive Cancellation Algorithm are extended based on the desired clutter of coefficient
Expectation, ECA-E) adopt and extension cancellation batch algorithms (Extensive Cancellation Algorithm
Batches, ECA-B) identical mode by clutter matrix and monitoring signals segmentation after, to reference signal delay process construct it is identical
The clutter matrix of dimension, per segment signal Least Square Method clutter coefficient is respectively adopted；The clutter system that every segment signal is estimated
Number seeks the clutter coefficient for expecting to obtain whole segment data；Unified clutter coefficient is back into every segment data carries out clutter recognition；Should
Method has outstanding rejection ability to static clutter, can be combined with ECA-B algorithms in actual applications, while suppressing static miscellaneous
Ripple and by force dynamic clutter, obtain more preferable clutter recognition effect.
Advantage of the invention is that：Algorithm has algorithm on the basis of clutter recognition performance is ensured by segment processing
There is more preferable parallel architecture, the calculating consumption of every part can be greatly reduced.Operation efficiency can be significantly improved during concurrent operation, is entered
And improve whole external radiation source radar system real time implementation performance.
Description of the drawings
Fig. 1 is ECA-E the and ECA-ES method structured flowcharts that the present invention is provided.
Fig. 2 is ECA-E＆B the and ECA-ES＆B method structured flowcharts that the present invention is provided.
Fig. 3 is the comparison diagram of method rejection in distance dimension that the present invention is provided.
Fig. 4 is the comparison diagram of method rejection in Doppler's dimension that the present invention is provided.
Fig. 5 is without the cross ambiguity function figure of clutter recognition in invention embodiment.
Fig. 6 is the cross ambiguity function figure in invention embodiment after ECA-E suppression.
Fig. 7 is the cross ambiguity function figure in invention embodiment after ECA-ES suppression.
Fig. 8 is the cross ambiguity function figure in invention embodiment after ECA-E＆B suppression.
Fig. 9 is the cross ambiguity function figure in invention embodiment after ECA-ES＆B suppression.
Specific embodiment
The present invention will be further described to combine accompanying drawing with specific embodiment below.
In the present embodiment, the external sort algorithm of selection is fm broadcast signal, and systematic sampling rate is 500kHz, per treatment
The coherent accumulation time is 1s.
As shown in figure 1, one kind proposed by the invention is included based on desired clutter extension cancellation method (ECA-E) of coefficient
Following steps：
Step one：By reference signal SrefWith monitoring signals SsurvB sections are divided into, i-th section of reference signal and monitoring signals are distinguished
For：With
Wherein, N is monitoring signals length, R be reference signal it is extra needed for sample number, and R is not less than distance element K that need to suppress；
Step 2：Reference signal after segmentation is pressed into unified rule construct clutter matrix, then i-th section of reference signal Srefi
The clutter matrix of construction is expressed as：Ci=B [Srefi DSrefi D2Srefi…DK-1Srefi].Wherein, B is incidence matrix, for carrying
Take the last of matrixRow element, is defined asD is displacement
Matrix, is defined as
Step 3：Segmentation least-squares estimation clutter matrix coefficient, the i-th segment data clutter matrix coefficient θiIt is estimated as
Step 4：Expectation is asked to every hop count clutter matrix coefficient according to estimates
Step 5：ReturnCarry out after clutter recognition, being in order stitched together per segment data to every segment data, obtain whole
The clutter recognition result of segment data.
When using ECA-ES algorithms, step 4 can be with abbreviation
The structure of ECA-E＆B and ECA-ES＆B algorithms is as shown in Fig. 2 comprise the steps of：
Step one：Using static clutter recognitions of the ECA-E or ECA-ES to front K distance element, and retain algorithm segmentation knot
Structure；
Step 2：Using ECA-B algorithms to the K near direct waveBIndividual distance element carries out clutter recognition, algorithm segmental structure
It is identical with step one；
Step 3：To in order be stitched together per segment data, obtain the clutter recognition result of whole segment data.
The performance of the present invention can be by relatively further illustrating with existing algorithm.
In the present embodiment, contrast algorithm is ECA, ECA-B and ECA-S.ECA-B, ECA-S, ECA-E and ECA-ES segments
Respectively bECA-B、bECA-S、bECA-EAnd bECA-ES.The sliding window element length of ECA-S algorithms is s.According to document (Sliding
extensive cancellation algorithm for disturbance removal in passive radar,in
IEEE Transactions on Aerospace and Electronic Systems,vol.52,no.3,pp.1309-
1326, June 2016) analysis method proposed in, when the noise signal of same suppression K distance elements, clutter recognition part
Amount of calculation C2(K,Ny) all same, the difference of each algorithm amount of calculation is mainly reflected in the amount of calculation of estimation filter coefficient part
C1(K,Nx) on.Wherein NxAnd NyRespectively it is used for the data length of filter coefficient estimation and filtering operation.
Table 1 compares the C of each algorithm1(K,Nx).Although ECA-E and ECA-ES algorithms amount of calculation is relative to ECA and ECA-B
It is increased slightly on the whole, but algorithm makes algorithm have more preferable parallel organization by the way that data are segmented in a large number, can significantly drop
The low calculating consumption per part, improves operation efficiency.Although ECA-S algorithms also can possess similar to ECA-E and ECA-ES algorithms
Pitch capability, however, to ensure that rejection, need substantial amounts of sliding window unit.Algorithm operation quantity is either on the whole still
ECA-E and ECA-ES algorithms are all far longer than per part.ECA-E＆B algorithms amount of calculation is ECA-E algorithms and ECA-B algorithm meters
Calculation amount sum.In ECA-E＆B algorithms, the distance element that ECA-B algorithms suppress is segmented far fewer than ECA-E algorithms through a large amount of,
ECA-B algorithms can be ignored in the amount of calculation that every part increases newly relative to ECA-E algorithms.Therefore ECA-E＆B algorithm amounts of calculation
It is similar to ECA-E algorithms.ECA-ES＆B algorithms are also the same, and amount of calculation is similar to ECA-ES algorithms.
The each algorithm C of table 11(K,Nx) compare
Introduce clutter recognition ratio (Clutter Attenuation, CA) and carry out assessment algorithm rejection, CA is defined asPinAnd PoutThe input signal and output signal energy of wave filter are represented respectively.
Reference signal is the fm broadcast signal that emulation is generated in the present embodiment, and signal to noise ratio is 70dB.Filter parameter is
bECA-B=10, bECA-S=20, bECA-E=bECA-ESSliding window length s=5e4 of=50, ECA-S algorithm.When front 10 distances of suppression
During first clutter, each algorithm is distinguished as shown in Figure 3 and Figure 4 in the CA curves in peacekeeping Doppler's dimension.From the figure, it can be seen that
ECA-E and ECA-ES algorithms possess static clutter outstanding rejection ability, and rejection is essentially identical with existing algorithm, but
It is weaker to dynamic clutter suppression capability.
The effect of the embodiment of the present invention can be further illustrated by the outfield experiments of track production.
In the present embodiment, segments bECA-E=bECA-ES=50, signal length N=5e5, R=K=200.In ECA-E＆B and
In ECA-ES＆B algorithms, ECA-E and ECA-ES algorithm partial parameters are constant, KB=4.
Fig. 5 is the cross ambiguity function figure before certain segment data clutter recognition, and target is fallen into oblivion by the secondary lobe of strong multipath clutter.
Fig. 6-9 sets forth using the filtered mutually fuzzy letter of ECA-E, ECA-ES, ECA-E＆B and ECA-ES＆B algorithm
Number figure.After the filtering of ECA-E and ECA-ES algorithms, strong static state clutter is suppressed, and target is highlighted, but near field still suffer from it is very strong
Dynamic clutter, have impact on the detection performance of close-in target.And ECA-E＆B and ECA-ES＆B algorithms be obtained in that it is more clean
Cross ambiguity function figure, close-in target is manifested.
Specific embodiment described herein is only explanation for example spiritual to the present invention.Technology neck belonging to of the invention
The technical staff in domain can be made various modifications to described specific embodiment or supplement or replaced using similar mode
Generation, but without departing from the spiritual of the present invention or surmount scope defined in appended claims.
Claims (3)
1. it is a kind of that cancellation method-ECA-E is extended based on the desired clutter of coefficient, it is characterised in that to comprise the following steps：
Step one：By reference signal SrefWith monitoring signals SsurvB sections are divided into, i-th section of reference signal and monitoring signals are distinguished
For：With
Wherein, N is monitoring signals length, R be reference signal it is extra needed for sample number, and R is not less than the distance element that need to suppress
K；
Step 2：Reference signal after segmentation is pressed into unified rule construct clutter matrix, then i-th section of reference signal SrefiConstruction
Clutter matrix be expressed as：Ci=B [Srefi DSrefi D2Srefi … DK-1Srefi]；
Wherein, B is incidence matrix, for extracting the last of matrixRow element, is defined as
D is shift matrix, is defined as
Step 3：Segmentation least-squares estimation clutter matrix coefficient, the i-th segment data clutter matrix coefficient θiIt is estimated as：
Step 4：Expectation is asked to every hop count clutter matrix coefficient according to estimates
Step 5：ReturnCarry out after clutter recognition, being in order stitched together per segment data to every segment data, obtain whole hop count
According to clutter recognition result.
2. according to claim 1 a kind of based on the desired clutter extension cancellation method of coefficient, it is characterised in that：The step
Weights when asking parameter to expect in rapid four can further simplify：When reference signal is stationary signal, signal power is approximately constant
When, the energy approximation after homogenous segmentations per segment signal is equal, it is therefore desirable for ask for expression formula can be with abbreviationAdopt
Take expression formula after simplifying and carry out the method for clutter recognition and be referred to as ECA-ES.
3. according to claim 1 and 2 a kind of based on the desired clutter extension cancellation method of coefficient, it is characterised in that：Will
ECA-E or ECA-ES algorithms are combined with extension cancellation batch algorithms-ECA-B, while suppress static clutter and by force dynamic clutter,
To obtain more preferable clutter recognition effect, this second-order filter method is referred to as ECA-E＆B, ECA-ES＆B, specifically comprising following
Step：
Step one：Using static clutter recognitions of the ECA-E or ECA-ES to front K distance element, and retain algorithm segmental structure；
Step 2：Using ECA-B algorithms to the K near direct waveBIndividual distance element carries out clutter recognition, algorithm segmental structure and step
Rapid one is identical；
Step 3：To in order be stitched together per segment data, obtain the clutter recognition result of whole segment data.
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