CN109471091A - Method for simultaneously resolving ambiguity, detecting and tracking intermediate repetition frequency PD radar - Google Patents
Method for simultaneously resolving ambiguity, detecting and tracking intermediate repetition frequency PD radar Download PDFInfo
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- CN109471091A CN109471091A CN201811317925.3A CN201811317925A CN109471091A CN 109471091 A CN109471091 A CN 109471091A CN 201811317925 A CN201811317925 A CN 201811317925A CN 109471091 A CN109471091 A CN 109471091A
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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
- 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
- G01S13/006—Theoretical aspects
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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
- 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
- G01S13/66—Radar-tracking systems; Analogous systems
Abstract
The invention discloses a method for simultaneously resolving ambiguity, detecting and tracking a medium repetition frequency PD radar, which comprises the following steps: preprocessing radar echoes; carrying out initialization processing; predicting; and (6) correcting. The method simultaneously carries out the fuzzy solution process and the detection tracking process under the high-density clutter background, thereby not only ensuring the correct detection probability, but also ensuring the quick and effective fuzzy solution method, having small calculated amount and low complexity, and solving the problems of high false alarm and high ghost image in the small target detection and tracking process.
Description
Technical field
The invention belongs to radar signal processing field, in particular to a kind of middle repetition PD radar simultaneously ambiguity solution and detection with
Track method.
Background technique
There is distance or Doppler measurement are fuzzy under different repetition rates for PD (pulse Doppler) radar.Middle heavy
In frequency PD radar, target range and speed of concern are typically all fuzzy.Common ambiguity solution method is that alternate emission is more
A PRF, then fuzzy to eliminate to the fuzzy measurement value progress relevant treatment of each PRF, common ambiguity solution algorithm includes China
Remainder theorem, Hovanessian algorithm and clustering algorithm.During ambiguity solution, exist by real goal generate measurement,
" ghost image " problem caused by the false-alarm that measurement, noise or the clutter that other targets generate generate is associated, and existing solution mould
Formulating method requires the measurement number of detection output to want sufficiently small, otherwise can not handle since the ghost image number of generation is excessive.
Ghost image can be rejected using some additional criterion, such as select to measure or using most by minimizing the variance between measurement
Maximum-likelihood estimation method, but the calculation amount of these methods and complexity are exponentially incremented by again with the increase of ghost image number, it is difficult
To ensure ambiguity solution precision.
Under high density clutter background, low noise/miscellaneous usually requires radar using a lower thresholding than condition
To guarantee the correct detection probability of target, and low threshold is then easy to cause the generation of a large amount of false-alarms, causes conventional ambiguity solution side
Method failure.Ambiguity solution process is combined consider it is one of the possible approaches for solving the above problem under low signal-to-noise ratio with detecting and tracking.
Based on the thought, ambiguity solution processing method under the conditions of low noise/miscellaneous ratio mainly has at present: (1) Kramer et al.
“Track-Before-Detect processing for a range-ambiguousradar”(IEEE
International Radar Conference collection of thesis, 1993 the 113-116 pages) propose it is a kind of based on Dynamic Programming
Detection before tracking, after DP-TBD use Chinese remainder theorem fuzzy distance solution.But this method is substantially still
It is so that target detection and ambiguity solution are divided into two independent process, improves the detection of Small object using TBD method in context of detection
Probability, and fuzzy number is then solved using remainder theorem in terms of ambiguity solution.The disadvantages of the method are as follows ambiguity solution process cannot be with inspection
Survey process carries out simultaneously, and as TBD detects increasing for output measurement number, remainder theorem can not correctly solve fuzzy number, when
When detection the number of output is excessive, ambiguity solution processing can not be carried out.(2) " the Multitarget particle of Bocquel et al.
filter addressing ambiguous radar data in TBD”(IEEE International Radar
Conference collection of thesis, 2012 the 575-580 pages) propose a multiple target PF-TBD for distance-Doppler radar
Filter, distance and Doppler ambiguity-resolution combine progress with PF-TBD operation.The disadvantages of the method are as follows when existing due to endless
U.S. detection process cause false-alarm and target missing inspection and target the case where observation interval appears or disappears when, ambiguity solution and more mesh
Mark PF-TBD (detects) Combined Treatment before particle filter-tracking can not adapt to the discontinuous situation of detection of target, under treatment effect
Drop is quickly.
Summary of the invention
It is an object of the present invention in view of the above shortcomings of the prior art, a kind of middle repetition PD radar is provided while solving mould
Ambiguity solution process is carried out simultaneously with detecting and tracking process, was both guaranteed under high density clutter background with detecting and tracking method by paste
Correct detection probability, and keep ambiguity solution method fast and effective, calculation amount is small, complexity is low, solve small target deteection with
Existing high false-alarm, high ghost problems during track.
In order to solve the above technical problems, the technical scheme adopted by the invention is that:
A kind of middle repetition PD radar ambiguity solution and detecting and tracking method simultaneously, its main feature is that the following steps are included:
Step A. pre-processes radar return:
If the state equation of target is xk=fk-1(xk-1,wk-1), wherein dbjective state vector is xk=[rk,vk]T, rkFor
Distance of the target in time step k, vkIt is target in the doppler velocity of time step k, corresponding pulse repetition period (PRF) is fk；
Echo is received to target seeker to handle, and obtains the observation set in a frameWherein
zk,i=[rk,i,vk,i]TFor the observation of single target number, corresponding not fuzzy ranging range is ruk=c/ (2fk), it is corresponding
The not fuzzy range that tests the speed be vuk=fkc/(2fc), mkFor the number of observation；
Step B. initialization process: setting target birth probability pb, survival probability ps, initial target existing probability p0|0, inspection
Survey Probability pD, particle number used in filtering is N, and newborn population is B；When k=0, primary is generated
Step C. prediction: step C1~C3 is executed:
Step C1, by pk-1|k-1、Existing probability p is carried out according to the following formulak|k-1Prediction: pk|k-1=pb(1-
pk-1|k-1)+pspk-1|k-1；
Step C2, it is N number of to retain particleAccording to state transition functionBy the state equation of target
Prediction generation is carried out, wherein wk-1For process noise sequence, corresponding weight is unanimously
Step C3, B newborn particleBy to newborn density bk|k-1(x) sampling acquisition is carried out, wherein newborn close
Spend bk|k-1(x) it is being uniformly distributed in sensor field of view:
1) by observing Zk-1Randomly choose a measurement z=[r, v]T；
2) by gathering 0 ..., a range ambiguity number l is randomly choosed in L；
3) by set-J ..., a doppler ambiguity number m is randomly choosed in K；
4) bySampling obtains w, bySampling obtains u；
5) it samples to obtain by the state equation of targetWherein x'=[r+lruk-1+w,v+mvuk-1+u]T；
The corresponding weight of newborn particle is unanimously
Step D. amendment: step D1~D4 is executed:
Step D1, by particleObserve Zk, likelihood ratio is calculated according to the following formula
Wherein c (z)=1/V=1/ (c2/(4fc)), fcFor carrier frequency；
Step D2, according toUpdate weight；
Step D3 sums to weight:
Step D4 estimates target existing probability according to the following formula:
Step E. estimation: step E1~E4 is executed:
Step E1 obtains normalized weight by following formula:
Step E2 carries out system resampling processing: to n=1~N, with probabilitySelect jn∈ { 1 ..., N+B } is obtained
Step E3, works as pk|kMore than certain thresholding Th ∈ (0,1), then determine that target is detected；
Step E4 estimates to obtain target-like using Minimum Mean Squared Error estimation device (MMSE) in the presence of detecting target
State:
By the above process, by under stochastic finite collection frame to clutter under target environment, imperfect detection causes
False-alarm and missing inspection and treatment process in target appearing and subsiding be described, improve the accuracy of data modeling and suitable
The property used；By using full Bayesian filter, realizes target existing probability and obtained with the recurrence of combining of state estimation；By using
Particle filter realization rate obtains the Fast implementation of Bernoulli Jacob's filter；It is tracked and is solved by Bayes's joint-detection
Blur method realizes under the conditions of clutter rate is 200 and accurately estimates the effective detecting and tracking and fuzzy number of target.
Compared with prior art, the present invention is same by ambiguity solution process and detecting and tracking process under high density clutter background
Shi Jinhang not only ensure that correct detection probability, but also keep ambiguity solution method fast and effective, and calculation amount is small, and complexity is low, solve small
Existing high false-alarm, high ghost problems during object detecting and tracking.
Detailed description of the invention
Fig. 1 is flow chart of the present invention.
Fig. 2 is test input and target measurement and false alarm condition.
Fig. 3 is target existing probability estimated value in treatment process.
Fig. 4 is distance and Doppler's evaluated error in treatment process.
Fig. 5 is the average performance times of each filter step in Bayesian filter.
Specific embodiment
With reference to the accompanying drawing with example to ambiguity solution and the inspection simultaneously of middle repetition PD radar under high density clutter of the present invention
Tracking is surveyed to be further elaborated.
Radar carrier frequency f in this examplecFor 10GHz, be used alternatingly two repetitions in each time step, PRF1=21kHz and
PRF2=31kHz, PRF1 are walked in odd time, and PRF2 is walked in even time.Wherein interested maximum target distance is rmax=
4ru1, i.e. L=4, the positive and negative doppler velocity of maximum interested is respectively 2vu2With -2vu2, i.e. J=K=2.Corresponding parameter is as follows
Shown in table:
| Parameter | ru1 | vu1 | ru2 | vu2 | rmax | vmax |
| Value | 7.1429km | 157.5m/s | 4.8387km | 232.5m/s | 28.572km | ±465m/s |
Fig. 1 gives flow chart of the invention, includes the following steps:
Step A. pre-processes radar return:
Totally 60 time steps, target are introduced into treatment process in time step 11, time step 51 be deleted, initial target away from
From for 7km, initial target doppler velocity is 340m/s.
Echo is received to target seeker to handle, and obtains observation setAs shown in Fig. 2, black
Color '+' measured for target generation, grey '+' it is false-alarm.It can be seen that target generate measurement be submerged in intensive false-alarm and
It is difficult to visually be found.
Step B. initialization process: setting target birth probability pb=0.05, survival probability ps=0.95, initial target is deposited
In Probability p0|0=0.1, detection probability pD=0.95, particle number used in filtering is N=2000, newborn population
For B=2000.；When k=0, primary is generated
Step C. prediction: step C1~C3 is executed:
Step C1, by pk-1|k-1、Existing probability p is carried out according to the following formulak|k-1Prediction: pk|k-1=pb(1-
pk-1|k-1)+pspk-1|k-1；
Step C2, it is N number of to retain particleAccording to state transition functionBy the state side of target
Cheng Jinhang prediction generates, wherein wk-1For process noise sequence, corresponding weight is unanimously
Step C3, B newborn particleBy to newborn density bk|k-1(x) sampling acquisition is carried out, wherein newborn close
Spend bk|k-1(x) it is being uniformly distributed in sensor field of view:
1) by observing Zk-1Randomly choose a measurement z=[r, v]T；
2) by gathering 0 ..., a range ambiguity number l is randomly choosed in L；
3) by set-J ..., a doppler ambiguity number m is randomly choosed in K；
4) bySampling obtains w, bySampling obtains u；
5) it samples to obtain by the state equation of targetWherein x'=[r+lruk-1+w,v+mvuk-1+u]T；
The corresponding weight of newborn particle is unanimously
Step D. amendment: step D1~D4 is executed:
Step D1, by particleObserve Zk, likelihood ratio is calculated according to the following formula
Wherein c (z)=1/V=1/ (c2/(4fc)), fcFor carrier frequency；
Step D2, according toUpdate weight；
Step D3 sums to particle weights:
Step D4 estimates target existing probability according to the following formula:Target existing probability estimated value
At any time spacer step variation relation as shown in figure 3, visual target time step 11 appearance after can after the delay of about 3 time steps quilt
It detects, pk|kIt securely maintains in a higher value, is reduced near 0 after target disappearance.
Step E. estimation: step E1~E4 is executed:
Step E1 obtains normalized weight by following formula:
Step E2 carries out system resampling processing: to n=1~N, with probabilitySelect jn∈ { 1 ..., N+B } is obtained
Step E3, works as pk|kMore than certain thresholding Th ∈ (0,1), then determine that target is detected；
Step E4 estimates to obtain target-like using Minimum Mean Squared Error estimation device (MMSE) in the presence of detecting target
State:Distance and Doppler's evaluated error change with time relationship such as in dbjective state component
Shown in Fig. 4, it is seen that distance and Doppler's estimation with the increase of time step converge to true value, are successfully realized distance and how general
Strangle ambiguity solution.
It gives the present invention with tracking process flow, Fig. 5 is combined according to ambiguity solution simultaneously and is walked with BPF method in each filtering
The execution time of (prediction, correction, resampling, estimation).Show that two methods are being predicted, resampling and estimation when the execution time
It is essentially identical, and the present invention is only the 30% of BPF the execution time needed for correction step, the overall execution time of the invention is also big
It is less than BPF and only 0.03s greatly, it can be seen that the present invention can be with real-time implementation.
To sum up, under high density clutter background, the present invention receives echo to target seeker and handles, with single target away from
From information and doppler information as a message sample, target information sample set is formed, in ambiguity solution process and detecting and tracking
In the process, particle filter thinking is introduced, completes the initialization, prediction, amendment, estimation iterative process of filter, is finally completed
Ambiguity solution and tracking while target range and doppler information.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited to above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than limitation, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form, within these are all belonged to the scope of protection of the present invention.
Claims (1)
1. a kind of middle repetition PD radar while ambiguity solution and detecting and tracking method, which comprises the following steps:
Step A. pre-processes radar return:
If the state equation of target is xk=fk-1(xk-1,wk-1), wherein dbjective state vector is xk=[rk,vk]T, rkFor target
In the distance of time step k, vkIt is target in the doppler velocity of time step k, the corresponding pulse repetition period is fk；
Echo is received to target seeker to handle, and obtains the observation set in a frameWherein zk,i=
[rk,i,vk,i]TFor the observation of single target number, corresponding not fuzzy ranging range is ruk=c/ (2fk), corresponding not mould
Paste tests the speed range as vuk=fkc/(2fc), mkFor the number of observation；
Step B. initialization process: setting target birth probability pb, survival probability ps, initial target existing probability p0|0, detection is generally
Rate pD, particle number used in filtering is N, and newborn population is B；When k=0, primary is generated
Step C. prediction: step C1~C3 is executed:
Step C1, by pk-1|k-1、Existing probability p is carried out according to the following formulak|k-1Prediction: pk|k-1=pb(1-pk-1|k-1)
+pspk-1|k-1；
Step C2, it is N number of to retain particleAccording to state transition functionBy target state equation into
Row prediction generates, wherein wk-1For process noise sequence, corresponding weight is unanimously
Step C3, B newborn particleBy to newborn density bk|k-1(x) sampling acquisition is carried out, wherein newborn density
bk|k-1(x) it is being uniformly distributed in sensor field of view:
1) by observing Zk-1Randomly choose a measurement z=[r, v]T；
2) by gathering 0 ..., a range ambiguity number l is randomly choosed in L；
3) by set-J ..., a doppler ambiguity number m is randomly choosed in K；
4) bySampling obtains w, bySampling obtains u；
5) it samples to obtain by the state equation of targetWherein x'=[r+lruk-1+w,v+mvuk-1+u]T；
The corresponding weight of newborn particle is unanimously
Step D. amendment: step D1~D4 is executed:
Step D1, by particleObserve Zk, likelihood ratio is calculated according to the following formula
Wherein c (z)=1/V=1/ (c2/(4fc)), fcFor carrier frequency；
Step D2, according toUpdate weight；
Step D3 sums to weight:
Step D4 estimates target existing probability according to the following formula:
Step E. estimation: step E1~E4 is executed:
Step E1 obtains normalized weight by following formula:
Step E2 carries out system resampling processing: to n=1~N, with probabilitySelect jn∈ { 1 ..., N+B } is obtained
Step E3, works as pk|kMore than certain thresholding Th ∈ (0,1), then determine that target is detected；
Step E4 estimates to obtain dbjective state using Minimum Mean Squared Error estimation device in the presence of detecting target:
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Cited By (4)
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| CN110726988A (en) * | 2019-10-30 | 2020-01-24 | 中国人民解放军海军航空大学 | Distance and speed fuzzy mutual solution method for detecting hypersonic target by PD radar |
| CN112363144A (en) * | 2020-11-27 | 2021-02-12 | 西安空间无线电技术研究所 | Distance fuzzy and azimuth fuzzy identification method for ring scan radar |
| CN117471449A (en) * | 2023-12-27 | 2024-01-30 | 中国电子科技集团公司第十四研究所 | Single group PD tracking method suitable for maneuvering target |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110456315A (en) * | 2019-08-29 | 2019-11-15 | 西安电子工程研究所 | A kind of irregular repetition object detection method based on position prediction |
| CN110456315B (en) * | 2019-08-29 | 2023-03-07 | 西安电子工程研究所 | Position prediction-based stagger repetition frequency target detection method |
| CN110726988A (en) * | 2019-10-30 | 2020-01-24 | 中国人民解放军海军航空大学 | Distance and speed fuzzy mutual solution method for detecting hypersonic target by PD radar |
| CN110726988B (en) * | 2019-10-30 | 2021-08-27 | 中国人民解放军海军航空大学 | Distance and speed fuzzy mutual solution method for detecting hypersonic target by PD radar |
| CN112363144A (en) * | 2020-11-27 | 2021-02-12 | 西安空间无线电技术研究所 | Distance fuzzy and azimuth fuzzy identification method for ring scan radar |
| CN117471449A (en) * | 2023-12-27 | 2024-01-30 | 中国电子科技集团公司第十四研究所 | Single group PD tracking method suitable for maneuvering target |
| CN117471449B (en) * | 2023-12-27 | 2024-03-22 | 中国电子科技集团公司第十四研究所 | Single group PD tracking method suitable for maneuvering target |
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