CN110109091A - A kind of passive radar method for parameter estimation and device for high-speed target - Google Patents
A kind of passive radar method for parameter estimation and device for high-speed target Download PDFInfo
- Publication number
- CN110109091A CN110109091A CN201910436354.3A CN201910436354A CN110109091A CN 110109091 A CN110109091 A CN 110109091A CN 201910436354 A CN201910436354 A CN 201910436354A CN 110109091 A CN110109091 A CN 110109091A
- Authority
- CN
- China
- Prior art keywords
- signal
- frequency
- parameter estimation
- domain
- time dimension
- 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
- 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
- G01S13/50—Systems of measurement based on relative movement of target
Abstract
The present invention relates to a kind of passive radar method for parameter estimation and device for high-speed target.This method obtains the echo signal that two passive radars receive, and using one of signal as reference signal, carries out pulse compression to two signals received；Frequency-domain transform is carried out in fast time dimension to the signal that pulse is compressed, and frequency domain cross-correlation calculation is carried out to the signal that frequency-domain transform obtains；The signal that frequency domain cross-correlation obtains is carried out becoming mark Fourier transformation in slow time dimension, obtains the frequency-domain transform result of slow time dimension；The frequency-domain transform result of slow time dimension is subjected to inverse Fourier transform in distance domain and takes peak value, the initial distance difference of two passive radars of corresponding target velocity and target range is as parameter estimation result when taking peak value, realize the Combined estimator of signal initial distance and speed, without knowing signal form and centre frequency, without one centre frequency of estimation, so that obtained estimates of parameters is more accurate.
Description
Technical field
The present invention relates to passive radar signal processing technology field, especially a kind of passive radar for high-speed target is joined
Number estimation method and device.
Background technique
Passive radar itself non-radiating electromagnetic wave, and directly receive the electromagnetic wave that target is radiated carry out parameter Estimation with
Positioning clearing hair, this special working principle makes it compared to active radar system, with concealment is high, spreadability is good, behaviour
Work is low with maintenance cost, is not take up the advantages that frequency spectrum resource,, will after receiving station receives signal in multistation Passive Radar System
It sends reference station to, and reference station carries out signal analysis.
Parameter Estimation Precision is proportional to signal observation time, and extends observation time and parameter Estimation essence not only can be improved
Degree, and weak target signal accumulation may be implemented in order to moving-target detection.But high-speed moving object, such as trajectory are led
Bullet, Hypersonic Aircraft, high-altitude high-performance cruise guided missile, near space vehicle etc., the extension of integration time will lead to distance and move
It is dynamic, cause backward energy to disperse, detection performance deteriorates.With this condition, it needs to compensate migration, then carries out parameter Estimation, this
It is the key point that passive radar realizes accurate parameter Estimation under long-time observation condition.
Traditional parameters algorithm for estimating requires to know echo signal centre frequency when compensating migration, however in practical feelings
In condition, passive radar is difficult to know the centre frequency of echo signal when detecting target, this results in parameter Estimation that can not carry out,
A centre frequency is estimated even from conventional detection experience, and obtained parameter is also highly inaccurate.
Summary of the invention
It is passive to solve the object of the present invention is to provide a kind of passive radar method for parameter estimation for high-speed target
Echo signal centre frequency, which is not easy to obtain, during Radar Signal Processing causes parameter estimation result to there are problems that error；This hair
It is bright that a kind of passive radar parameter estimation apparatus for high-speed target is also provided, to solve in passive radar signal processing
Echo signal centre frequency, which is not easy to obtain, causes parameter estimation result to there are problems that error.
To achieve the goals above, the present invention provides a kind of passive radar method for parameter estimation for high-speed target, packet
Include following steps:
1) echo signal that receives of two passive radars is obtained, using one of signal as reference signal, to receiving
Two signals carry out pulse compression；
2) frequency-domain transform is carried out in fast time dimension to the signal that pulse is compressed, and to the signal that frequency-domain transform obtains
Carry out frequency domain cross-correlation calculation；
3) signal that frequency domain cross-correlation obtains is carried out becoming mark Fourier transformation in slow time dimension, obtains slow time dimension
Frequency-domain transform result；
4) the frequency-domain transform result of slow time dimension is subjected to inverse Fourier transform in distance domain, to the knot of inverse Fourier transform
Fruit takes peak value, and the initial distance difference of two passive radars of corresponding target velocity and target range is as parameter when taking peak value
Estimated result.
Beneficial effect is, by considering that is generated in passive radar target echo signal cumulative process asks across distance unit
Topic marks Fourier transformation using becoming, realizes the Combined estimator of signal initial distance and speed, therefore in above-mentioned calculating process
Without knowing signal form and centre frequency, without one centre frequency of estimation, so that obtained estimates of parameters is more
Precisely, in addition, use long time integration technology, realize it is relatively simple, and be not present blind speed secondary lobe the problems such as, high reliablity,
With preferable engineering practicability.
Further, in order to simplify subsequent calculating process, the echo signal that two passive radars receive is respectively
One signal and second signal, the first signal r1(t,tm) and second signal r2(t,tm) expression formula be respectively
r1(t,tm)=s (t) exp (j2 π fct)+n1(t)
r2(t,tm)=As (t- τ (tm))exp(j2πfc(t-τ(tm)))+n2(t)
In formula, t indicates fast time dimension, tmIndicate that slow time dimension, A are the relative amplitude of echo-signal, fcEmitted by target
The centre frequency of signal, j are imaginary unit, n1(t) and n2(t) the reception signal for respectively indicating the first signal and the second signal is made an uproar
Sound, the time delay that echo signal reaches two passive radars areWherein, c is propagation velocity of electromagnetic wave,
voFor echo signal speed, R0Initial distance for two passive radars of target range is poor.
Further, it according to the definition to the first signal and the second signal, is calculated to simplify, with the first letter in step 1)
Number it is reference signal, pulse compression, pulse boil down to is carried out to two signals receiving
It brings the expression formula of the first signal and the second signal into above formula, ignores noise, obtain
In formula, A1To finish the compressed signal amplitude of pulse, PrIt is two paths of signals through the compressed signal packet of extra pulse
It falls.
Further, in order to accurately carry out frequency domain cross-correlation to signal, pulse is compressed along fast time dimension t in step 2)
Fast Fourier Transform (FFT) i.e. frequency-domain transform is done, is obtained
Defining frequency domain cross-correlation is
By Sc(f,tm) above formula is substituted into, it obtains
Due to not included f in signal, frequency domain cross correlation results are
In formula, A2For Sc(f,tm) amplitude, fnFor the frequency delay factor.
Further, since long time integration technology is realized simply, to above-mentioned frequency domain cross correlation results slow in step 3)
Time dimension carries out change mark Fourier transformation and obtains signal P (fn,fm), formula is as follows:
In formula, fmIt is tmFourier transform pairs,It indicates to RIFAF(fn,tm) along tmBecome
Fourier transformation is marked, ξ is scaling factor.
Further, in order to accurately consider span from unit problem, by signal P (f in step 4)n,fm) carried out in distance domain
Inverse Fourier transform, as follows:
In formula, δ is impulse function, tnFor frequency delay factor fnInverse Fourier transform after the when domain representation factor.
Further, in order to accurately obtain estimation parameter, to the result G (t of inverse Fourier transform in step 4)n,fm) take peak
Value, due to G (tn,fm) in tnAnd fmIt is made of in dimension two impulse functions, therefore the position where maximum value is peak value, such as
Under:
In formula,WithRespectively R0And voEstimated value, tn,maxAnd fm,maxIt is respectively as G (tn,fm) when being maximized
TnAnd fm；WithAs parameter estimation result.
The present invention provide a kind of passive radar parameter estimation apparatus for high-speed target, including memory, processor with
And storage is in memory and the computer program that can run on a processor, when the processor executes described program realization with
Lower step:
1) echo signal that receives of two passive radars is obtained, using one of signal as reference signal, to receiving
Two signals carry out pulse compression；
2) frequency-domain transform is carried out in fast time dimension to the signal that pulse is compressed, and to the signal that frequency-domain transform obtains
Carry out frequency domain cross-correlation calculation；
3) signal that frequency domain cross-correlation obtains is carried out becoming mark Fourier transformation in slow time dimension, obtains slow time dimension
Frequency-domain transform result；
4) the frequency-domain transform result of slow time dimension is subjected to inverse Fourier transform in distance domain, to the knot of inverse Fourier transform
Fruit takes peak value, and the initial distance difference of two passive radars of corresponding target velocity and target range is as parameter when taking peak value
Estimated result.
Beneficial effect is, by considering that is generated in passive radar target echo signal cumulative process asks across distance unit
Topic marks Fourier transformation using becoming, realizes the Combined estimator of signal initial distance and speed, therefore in above-mentioned calculating process
Without knowing signal form and centre frequency, without one centre frequency of estimation, so that obtained estimates of parameters is more
Precisely, in addition, use long time integration technology, realize it is relatively simple, and be not present blind speed secondary lobe the problems such as, high reliablity,
With preferable engineering practicability.
Further, in order to simplify subsequent calculating process, the echo signal that two passive radars of the device receive
Respectively the first signal and the second signal, the first signal r1(t,tm) and second signal r2(t,tm) expression formula be respectively
r1(t,tm)=s (t) exp (j2 π fct)+n1(t)
r2(t,tm)=As (t- τ (tm))exp(j2πfc(t-τ(tm)))+n2(t)
In formula, t indicates fast time dimension, tmIndicate that slow time dimension, A are the relative amplitude of echo-signal, fcEmitted by target
The centre frequency of signal, j are imaginary unit, n1(t) and n2(t) the reception signal for respectively indicating the first signal and the second signal is made an uproar
Sound, the time delay that echo signal reaches two passive radars areWherein, c is propagation velocity of electromagnetic wave,
voFor echo signal speed, R0Initial distance for two passive radars of target range is poor.
Further, it according to the definition to the first signal and the second signal, is calculated to simplify, in the step 1) of the device
Using the first signal as reference signal, pulse compression, pulse boil down to are carried out to two signals received
It brings the expression formula of the first signal and the second signal into above formula, ignores noise, obtain
In formula, A1To finish the compressed signal amplitude of pulse, PrIt is two paths of signals through the compressed signal packet of extra pulse
It falls.
Further, in order to accurately carry out frequency domain cross-correlation to signal, in the step 2) of the device to pulse compression along
Fast time dimension t does Fast Fourier Transform (FFT) i.e. frequency-domain transform, obtains
Defining frequency domain cross-correlation is
By Sc(f,tm) above formula is substituted into, it obtains
Due to not included f in signal, frequency domain cross correlation results are
In formula, A2For Sc(f,tm) amplitude, fnFor the frequency delay factor.
Further, since long time integration technology is realized simply, to above-mentioned frequency domain cross-correlation in the step 3) of the device
As a result change mark Fourier transformation is carried out in slow time dimension obtain signal P (fn,fm), formula is as follows:
In formula, fmIt is tmFourier transform pairs,It indicates to RIFAF(fn,tm) along tmIt carries out
Become mark Fourier transformation, ξ is scaling factor.
Further, in order to accurately consider span from unit problem, by signal P (f in the step 4) of the devicen,fm) away from
Delocalization carries out inverse Fourier transform, as follows:
In formula, δ is impulse function, tnFor frequency delay factor fnInverse Fourier transform after the when domain representation factor.
Further, in order to accurately obtain estimation parameter, to the result G of inverse Fourier transform in the step 4) of the device
(tn,fm) peak value is taken, due to G (tn,fm) in tnAnd fmIt is made of in dimension two impulse functions, therefore the position where maximum value is
It is as follows for peak value:
In formula,WithRespectively R0And voEstimated value, tn,maxAnd fm,maxIt is respectively as G (tn,fm) when being maximized
TnAnd fm；WithAs parameter estimation result.
Detailed description of the invention
Fig. 1 is the received schematic diagram of echo signal of the invention；
Fig. 2 is a kind of flow chart of passive radar method for parameter estimation for high-speed target of the invention；
Fig. 3 is echo signal accumulation result figure of the invention；
In figure, 1 is the first passive radar, and 2 be the second passive radar, and 3 be target.
Specific embodiment
The present invention will be further described in detail with reference to the accompanying drawing.
Embodiment of the method:
Passive radar target acquisition of the invention, as shown in Figure 1, the first passive radar 1 and the second passive radar 2 are for cutting
Obtain the radiation signal that target 3 is given off.
For the high-speed target signal, the present invention provides a kind of passive radar method for parameter estimation for high-speed target,
As shown in Figure 2, comprising the following steps:
1) echo signal that receives of two passive radars is obtained, using one of signal as reference signal, to receiving
Two signals carry out pulse compression.
2) frequency-domain transform is carried out in fast time dimension to the signal that pulse is compressed, and to the signal that frequency-domain transform obtains
Carry out frequency domain cross-correlation calculation.
3) signal that frequency domain cross-correlation obtains is carried out becoming mark Fourier transformation in slow time dimension, obtains slow time dimension
Frequency-domain transform result.
4) the frequency-domain transform result of slow time dimension is subjected to inverse Fourier transform in distance domain, to the knot of inverse Fourier transform
Fruit takes peak value, and the initial distance difference of two passive radars of corresponding target velocity and target range is as parameter when taking peak value
Estimated result.
The echo signal that two passive radars receive is respectively the first signal and the second signal, the first signal r1(t,tm)
With second signal r2(t,tm) expression formula be respectively
r1(t,tm)=s (t) exp (j2 π fct)+n1(t)
r2(t,tm)=As (t- τ (tm))exp(j2πfc(t-τ(tm)))+n2(t)
In formula, t indicates fast time dimension, tmIndicate that slow time dimension, A are the relative amplitude of echo-signal, fcEmitted by target
The centre frequency of signal, j are imaginary unit, n1(t) and n2(t) the reception signal for respectively indicating the first signal and the second signal is made an uproar
Sound, the time delay that echo signal reaches two passive radars areWherein, c is propagation velocity of electromagnetic wave,
voFor echo signal speed, R0For the difference of two passive radar initial distances of distance.
Using the first signal as reference signal in step 1), pulse compression, pulse compression are carried out to two signals received
For
It brings the expression formula of the first signal and the second signal into above formula, ignores noise, obtain
In formula, A1To finish the compressed signal amplitude of pulse, PrIt is two paths of signals through the compressed signal packet of extra pulse
It falls.
Pulse is compressed along fast time dimension t in step 2) and does Fast Fourier Transform (FFT) i.e. frequency-domain transform, is obtained
Defining frequency domain cross-correlation is
By Sc(f,tm) above formula is substituted into, it obtains
Due to not included f in signal, frequency domain cross correlation results are
In formula, A2For Sc(f,tm) amplitude, fnFor the frequency delay factor.
Change mark Fourier transformation is carried out in slow time dimension to above-mentioned frequency domain cross correlation results in step 3) and obtains signal P
(fn,fm), formula is as follows:
In formula, fmIt is tmFourier transform pairs,It indicates to RIFAF(fn,tm) along tmIt carries out
Become mark Fourier transformation, ξ is scaling factor.
By signal P (f in step 4)n,fm) distance domain carry out inverse Fourier transform, it is as follows:
In formula, δ is impulse function, tnFor frequency delay factor fnInverse Fourier transform after the when domain representation factor.
To the result G (t of inverse Fourier transform in step 4)n,fm) peak value is taken, due to G (tn,fm) in tnAnd fmBy two in dimension
A impulse function composition, therefore the position where maximum value is peak value, it is as follows:
In formula,WithRespectively R0And voEstimated value, tn,maxAnd fm,maxIt is respectively as G (tn,fm) when being maximized
TnAnd fm；WithAs parameter estimation result, finally realizeWithJoint parameter estimation.
As shown in Figure 3, it can be seen that target echo energy has been concentrated in a bit, to improve the faint letter of system detection
Number ability, and the position where peak value is the parameter estimation result of targetWith
Installation practice:
The present invention provide a kind of passive radar parameter estimation apparatus for high-speed target, including memory, processor with
And the computer program that can be run in memory and on a processor is stored, processor realizes that the above method is real when executing program
Apply method and step in example.
Specific embodiment of the present invention is presented above, but the present invention is not limited to described embodiment.
The technological means in above-described embodiment is converted by the way of being readily apparent that those skilled in the art, is replaced,
Modification, and play the role of with the present invention in relevant art means it is essentially identical, realization goal of the invention it is also essentially identical,
The technical solution formed in this way is to be finely adjusted to be formed to above-described embodiment, and this technical solution still falls within protection of the invention
In range.
Claims (8)
1. a kind of passive radar method for parameter estimation for high-speed target, which comprises the following steps:
1) echo signal that two passive radars receive is obtained, using one of signal as reference signal, to two received
A signal carries out pulse compression；
2) frequency-domain transform is carried out in fast time dimension to the signal that pulse is compressed, and the signal that frequency-domain transform obtains is carried out
Frequency domain cross-correlation calculation；
3) signal that frequency domain cross-correlation obtains is carried out becoming mark Fourier transformation in slow time dimension, obtains the frequency domain of slow time dimension
Transformation results；
4) the frequency-domain transform result of slow time dimension is subjected to inverse Fourier transform in distance domain, the result of inverse Fourier transform is taken
Peak value, the initial distance difference of two passive radars of corresponding target velocity and target range is as parameter Estimation when taking peak value
As a result.
2. the passive radar method for parameter estimation according to claim 1 for high-speed target, which is characterized in that two nothings
The echo signal that source radar receives is respectively the first signal and the second signal, the first signal r1(t,tm) and second signal r2(t,
tm) expression formula be respectively
r1(t,tm)=s (t) exp (j2 π fct)+n1(t)
r2(t,tm)=As (t- τ (tm))exp(j2πfc(t-τ(tm)))+n2(t)
In formula, t indicates fast time dimension, tmIndicate that slow time dimension, A are the relative amplitude of echo-signal, fcSignal is emitted by target
Centre frequency, j is imaginary unit, n1(t) and n2(t) the reception signal noise of the first signal and the second signal, mesh are respectively indicated
Mark signal reaches the time delays of two passive radars and isWherein, c is propagation velocity of electromagnetic wave, voFor
Echo signal speed, R0Initial distance for two passive radars of target range is poor.
3. the passive radar method for parameter estimation according to claim 2 for high-speed target, which is characterized in that step 1)
In using the first signal as reference signal, pulse compression, pulse boil down to are carried out to two signals receiving
It brings the expression formula of the first signal and the second signal into above formula, ignores noise, obtain
In formula, A1To finish the compressed signal amplitude of pulse, PrIt is fallen for two paths of signals through the compressed signal packet of extra pulse.
4. the passive radar method for parameter estimation according to claim 3 for high-speed target, which is characterized in that step 2)
In to pulse compression along fast time dimension t carry out Fast Fourier Transform, that is, frequency-domain transform, obtain
Defining frequency domain cross-correlation is
By Sc(f,tm) above formula is substituted into, it obtains
Due to not included f in signal, frequency domain cross correlation results are
In formula, A2For Sc(f,tm) amplitude, fnFor the frequency delay factor.
5. the passive radar method for parameter estimation according to claim 4 for high-speed target, which is characterized in that step 3)
In to above-mentioned frequency domain cross correlation results slow time dimension carry out become mark Fourier transformation obtain signal P (fn,fm), formula is as follows:
In formula, fmIt is tmFourier transform pairs,It indicates to RIFAF(fn,tm) along tmIt carries out becoming mark Fu
In leaf transformation, ξ is scaling factor.
6. the passive radar method for parameter estimation according to claim 5 for high-speed target, which is characterized in that step 4)
It is middle by signal P (fn,fm) distance domain carry out inverse Fourier transform, it is as follows:
In formula, δ is impulse function, tnFor frequency delay factor fnInverse Fourier transform after the when domain representation factor.
7. the passive radar method for parameter estimation according to claim 6 for high-speed target, which is characterized in that step 4)
In to the result G (t of inverse Fourier transformn,fm) peak value is taken, due to G (tn,fm) in tnAnd fmBy two impulse function groups in dimension
At, therefore the position where maximum value is peak value, it is as follows:
In formula,WithRespectively R0And voEstimated value, tn,maxAnd fm,maxIt is respectively as G (tn,fm) t when being maximizedn
And fm；WithAs parameter estimation result.
8. a kind of passive radar parameter estimation apparatus for high-speed target, including memory, processor and it is stored in storage
In device and the computer program that can run on a processor, which is characterized in that the processor is realized such as when executing described program
The passive radar method for parameter estimation of high-speed target is directed to described in any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910436354.3A CN110109091B (en) | 2019-05-23 | 2019-05-23 | Passive radar parameter estimation method and device for high-speed target |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910436354.3A CN110109091B (en) | 2019-05-23 | 2019-05-23 | Passive radar parameter estimation method and device for high-speed target |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110109091A true CN110109091A (en) | 2019-08-09 |
| CN110109091B CN110109091B (en) | 2021-11-09 |
Family
ID=67491895
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910436354.3A Active CN110109091B (en) | 2019-05-23 | 2019-05-23 | Passive radar parameter estimation method and device for high-speed target |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110109091B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111624574A (en) * | 2020-07-29 | 2020-09-04 | 绵阳市游仙区创新科技产业技术研究院 | Target detection method, system, storage medium and device for weak target detection |
| CN111669191A (en) * | 2020-04-25 | 2020-09-15 | 中国人民解放军战略支援部队信息工程大学 | Short wave ultrashort wave signal enhancement method based on distributed receiving system |
| CN112748427A (en) * | 2020-12-09 | 2021-05-04 | 中国人民解放军战略支援部队信息工程大学 | Joint estimation method for range difference and range difference change rate of pulse signal |
| CN116509382A (en) * | 2023-07-03 | 2023-08-01 | 深圳市华翌科技有限公司 | Human body activity intelligent detection method and health monitoring system based on millimeter wave radar |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010286337A (en) * | 2009-06-11 | 2010-12-24 | Furuno Electric Co Ltd | Correlation processing device, correlation processing method, pulse compression device and target detector |
| US20120287964A1 (en) * | 2010-01-11 | 2012-11-15 | Bae Systems Plc | Method of providing a radar high range resolution profile |
| KR101252485B1 (en) * | 2012-10-09 | 2013-04-09 | 국방과학연구소 | Method of fast imaging for bistatic radar and apparatus of the same |
| CN103176178A (en) * | 2013-02-04 | 2013-06-26 | 中国人民解放军海军航空工程学院 | Radar moving target radon-fractional Fourier transform long-time phase-coherent accumulation detection method |
| CN103399310A (en) * | 2013-08-07 | 2013-11-20 | 中国人民解放军海军航空工程学院 | Method for detecting radar weak moving target based on PD (Phase Differentiation) RLVD (Radon-Lv Distribution) |
| EP2677343A1 (en) * | 2011-02-18 | 2013-12-25 | Mitsubishi Electric Corporation | Passive radar device |
| CN107290724A (en) * | 2017-06-02 | 2017-10-24 | 北京理工大学 | A kind of high dynamic signal method for parameter estimation based on delay correlation function |
| CN107607934A (en) * | 2017-08-31 | 2018-01-19 | 清华大学 | A kind of time difference, frequency difference, frequency difference rate of change combined estimation method |
| CN108549067A (en) * | 2018-07-27 | 2018-09-18 | 电子科技大学 | A kind of phase-coherent accumulation detection method being applied to three rank maneuvering targets |
| CN109031261A (en) * | 2018-06-01 | 2018-12-18 | 中国人民解放军战略支援部队信息工程大学 | A kind of time difference estimation method and device |
| CN109581318A (en) * | 2019-01-10 | 2019-04-05 | 中国人民解放军海军航空大学 | Radar highly maneuvering target phase-coherent accumulation detection method based on time reversal nonuniform sampling |
-
2019
- 2019-05-23 CN CN201910436354.3A patent/CN110109091B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010286337A (en) * | 2009-06-11 | 2010-12-24 | Furuno Electric Co Ltd | Correlation processing device, correlation processing method, pulse compression device and target detector |
| US20120287964A1 (en) * | 2010-01-11 | 2012-11-15 | Bae Systems Plc | Method of providing a radar high range resolution profile |
| EP2677343A1 (en) * | 2011-02-18 | 2013-12-25 | Mitsubishi Electric Corporation | Passive radar device |
| KR101252485B1 (en) * | 2012-10-09 | 2013-04-09 | 국방과학연구소 | Method of fast imaging for bistatic radar and apparatus of the same |
| CN103176178A (en) * | 2013-02-04 | 2013-06-26 | 中国人民解放军海军航空工程学院 | Radar moving target radon-fractional Fourier transform long-time phase-coherent accumulation detection method |
| CN103399310A (en) * | 2013-08-07 | 2013-11-20 | 中国人民解放军海军航空工程学院 | Method for detecting radar weak moving target based on PD (Phase Differentiation) RLVD (Radon-Lv Distribution) |
| CN107290724A (en) * | 2017-06-02 | 2017-10-24 | 北京理工大学 | A kind of high dynamic signal method for parameter estimation based on delay correlation function |
| CN107607934A (en) * | 2017-08-31 | 2018-01-19 | 清华大学 | A kind of time difference, frequency difference, frequency difference rate of change combined estimation method |
| CN109031261A (en) * | 2018-06-01 | 2018-12-18 | 中国人民解放军战略支援部队信息工程大学 | A kind of time difference estimation method and device |
| CN108549067A (en) * | 2018-07-27 | 2018-09-18 | 电子科技大学 | A kind of phase-coherent accumulation detection method being applied to three rank maneuvering targets |
| CN109581318A (en) * | 2019-01-10 | 2019-04-05 | 中国人民解放军海军航空大学 | Radar highly maneuvering target phase-coherent accumulation detection method based on time reversal nonuniform sampling |
Non-Patent Citations (7)
| Title |
|---|
| JIANCHENG ZHANG: "Novel Fast Coherent Detection Algorithm for Radar Maneuvering Target With Jerk Motion", 《IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING》 * |
| JIBIN ZHENG: "Radar High-Speed Target Detection Based on the Scaled Inverse Fourier Transform", 《IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING》 * |
| TAKAHASHI, R等: "Subband Cross-Correlation Processing with Interference Mitigation for Passive Bistatic Radar", 《2014 IEEE RADAR CONFERENCE IEEE RADAR CONFERENCE》 * |
| ZHIXIN LIU: "A Novel Interpolation Method for TDOA and FDOA Estimation based on Second-order Cone Programming", 《2018 19TH INTERNATIONAL RADAR SYMPOSIUM (IRS)》 * |
| 刘传梁: "基于傅里叶变换（FFT）算法的频率参数 RF 提取方法", 《信息周刊》 * |
| 周龙健: "运动双站多脉冲无源定位算法", 《航空学报》 * |
| 张南: "基于变标处理和分数阶傅里叶变换的运动目标检测算法", 《电子学报》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111669191A (en) * | 2020-04-25 | 2020-09-15 | 中国人民解放军战略支援部队信息工程大学 | Short wave ultrashort wave signal enhancement method based on distributed receiving system |
| CN111624574A (en) * | 2020-07-29 | 2020-09-04 | 绵阳市游仙区创新科技产业技术研究院 | Target detection method, system, storage medium and device for weak target detection |
| CN112748427A (en) * | 2020-12-09 | 2021-05-04 | 中国人民解放军战略支援部队信息工程大学 | Joint estimation method for range difference and range difference change rate of pulse signal |
| CN112748427B (en) * | 2020-12-09 | 2024-04-23 | 中国人民解放军战略支援部队信息工程大学 | Joint estimation method for distance difference and distance difference change rate of pulse signals |
| CN116509382A (en) * | 2023-07-03 | 2023-08-01 | 深圳市华翌科技有限公司 | Human body activity intelligent detection method and health monitoring system based on millimeter wave radar |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110109091B (en) | 2021-11-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110109091A (en) | A kind of passive radar method for parameter estimation and device for high-speed target | |
| CN106970371B (en) | A kind of object detection method based on Keystone and matched filtering | |
| CN107561508B (en) | Coherent accumulation detection method for uniformly accelerated moving target | |
| CN103323829B (en) | Based on the radar moving targets long-time phase-coherent accumulation detection method of Radon-fractional order ambiguity function | |
| CN104076351B (en) | Phase-coherent accumulation detection method for high-speed high maneuvering target | |
| CN106842128B (en) | The acoustics tracking and device of moving target | |
| CN107329138B (en) | Distance walking correction and coherent accumulation detection method for PD radar | |
| CN111736128B (en) | Phase-coherent accumulation method based on SKT-SIAF-MSCFT | |
| CN107831480A (en) | Missile-borne radar and the sane self-adapting clutter suppressing method of poor passage | |
| CN103018727A (en) | Sample-training-based non-stationary clutter suppression method of vehicle-mounted radar | |
| Zhao et al. | Cramer-Rao lower bounds for the joint delay-Doppler estimation of an extended target | |
| US9857455B2 (en) | Radar filter process using antenna patterns | |
| CN105510887A (en) | Method for inhibiting active suppressing jamming to airborne radar under clutter background | |
| CN104977567B (en) | A kind of adaptive launching beam forming method of OFDM monopulse radars | |
| CN106872969B (en) | Radar target angle estimation method based on MTD pulse accumulation and sliding processing | |
| CN109188385A (en) | High speed weak object detection method under clutter background | |
| CN112526474A (en) | FMCW radar range-velocity joint estimation method based on full-phase Fourier transform | |
| CN105738887A (en) | Airborne radar clutter power spectrum optimization method based on Doppler channel division | |
| CN104931946A (en) | Outer radiation source radar Doppler-time delay two-dimension double-threshold object detection method | |
| CN103412302B (en) | Multiple carrier frequency MISO radar target locating method based on priori knowledge | |
| CN112485772A (en) | Clutter suppression method for inter-pulse frequency agility radar | |
| CN106019243A (en) | Inter-pulse initial phase third-power modulation and FRFT (fractional Fourier transform)-based DRFM (digital radio frequency memory) interference detection and resisting method | |
| CN112987003B (en) | HFM signal separation method and system in active sonar | |
| CN109001671B (en) | Target detection and parameter estimation method and device for frequency hopping signal | |
| CN103809164B (en) | A kind of rear Doppler's optimum clutter suppression method of reconstructed reference passage |
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 |