CN106443614A - Hypersonic velocity target acceleration testing method - Google Patents

Hypersonic velocity target acceleration testing method Download PDF

Info

Publication number
CN106443614A
CN106443614A CN201610709771.7A CN201610709771A CN106443614A CN 106443614 A CN106443614 A CN 106443614A CN 201610709771 A CN201610709771 A CN 201610709771A CN 106443614 A CN106443614 A CN 106443614A
Authority
CN
China
Prior art keywords
matrix
spectral
row
value
data
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
Application number
CN201610709771.7A
Other languages
Chinese (zh)
Other versions
CN106443614B (en
Inventor
赵光辉
刘飞涛
沈方芳
石光明
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xidian Univ
Original Assignee
Xidian Univ
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Xidian Univ filed Critical Xidian Univ
Priority to CN201610709771.7A priority Critical patent/CN106443614B/en
Publication of CN106443614A publication Critical patent/CN106443614A/en
Application granted granted Critical
Publication of CN106443614B publication Critical patent/CN106443614B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S7/00Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41Details 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

Abstract

A hypersonic velocity target acceleration testing method is mainly used for solving the problems that the acceleration testing precision of the A hypersonic velocity target in the prior art is not high and the measurable scale is small. The method includes steps of (1) receiving echo data; (2) mixing treatment; (3) matched filtering; (4) phase difference of frequency domain; (5) structuring a spectrum coordinate matrix; (6) spectrum peak searching method; (7) calculating target acceleration; (8) outputting target acceleration to the system. By applying the frequency domain phase differential method, the acceleration factor in the echo signal phase can be effectively extracted, so that the method is high in accuracy and low in calculation complexity. By applying the spectral line searching method, the contradiction of acceleration fuzzy and maximum measurable acceleration can be effectively solved, thus the method has the advantage of big measurable zone. Through the treatment in the two-dimensional frequency domain, the invention is applicable to low signal-to-noise ratio.

Description

Hypersonic target measuring acceleration method
Technical field
The invention belongs to communication technical field, further relate to the hypersonic target detection technique of Radar Signal Processing One hypersonic target measuring acceleration method in field.The present invention utilizes the frequency domain information of Doppler radar echo signal to use Signal processing method estimates aimed acceleration, it is achieved ballistic missile defense, the hypersonic target detection in space.
Background technology
Traditional target radial acceleration estimation method, by calculating the target range of multiple cycle echo, constructs two Then rank difference equation utilizes least square method to calculate acceleration, but owing to range error is added in acceleration calculation, makes Become acceleration estimation value error bigger.
The paper that Jia Shuyi, kingdom are grand, Zhang Lei delivers at it " is estimated based on the maneuvering target radial acceleration of compressed sensing A kind of compressed sensing skill disclosed in meter " (system engineering and electronic technology, volume 35 the 9th phase page 1815~1820 in September, 2013) Art measures acceleration method.First the method sets up over-complete dictionary of atoms according to maneuvering target echo features, obtains signal Decomposition coefficient projection on over-complete dictionary of atoms, then utilizes an observing matrix to carry out lack sampling to the signal after decomposition, By solving the Least Square Solution under the conditions of a 1-norm constraint, extract the frequency modulation rate of signal, finally utilize radially Acceleration Formula realizes acceleration estimation.The weak point that the method exists is to need to build sufficiently large atom and just can carry High measurement accuracy, computation complexity is higher.
Paper " the pulse radar radial acceleration Study on Extraction Method that first Jian Hai, Wu Shangshang, Xu Xu, Yue Rui deliver at it With application " (play arrow with guidance journal, volume 34 the 3rd phase page 191~202 in June, 2014) disclosed in a kind of multinomial phse conversion With Short Time Fourier Transform method.First the method carries out polynomial-phase conversion and Short Time Fourier Transform to echo data, Obtain the Time-Frequency Information containing radial acceleration, then utilize gravity model appoach to extract target radial acceleration.The method exists not It in place of foot is, when target has high acceleration, it is impossible to realize acceleration ambiguity solution, scope can be surveyed little.
Content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, propose a kind of hypersonic target measuring acceleration method. The method makes full use of frequency domain phase difference and 2-d spectrum spectral line search method, solves measuring acceleration precision problem and acceleration mould Stick with paste not high problem.
The basic ideas of the object of the invention are:It is first depending on the thought that aimed acceleration is easy to extract in a frequency domain, pass through Frequency domain phase difference filters the phase place change causing because of target range, target velocity, the then scope with aimed acceleration to be measured Obtain the region of search, 2-d spectrum carries out spectral line search, it is achieved ambiguity solution process, finally solve target to be measured and accelerate Degree.
The present invention comprises the following steps that:
(1) it is received back to wave datum:
Gather the echo data that radar array element receives, and be stored in a matrix type in Installed System Memory;
(2) Frequency mixing processing:
Frequency mixing processing is carried out to echo data, obtains low-frequency data;
(3) according to the following formula, matched filtering is carried out to low-frequency data, obtain observing data matrix:
Y=H*X
Wherein, y represents observation data matrix, and H represents matched filtering function, and * represents convolution operation, and X represents low-frequency data;
(4) frequency domain phase difference:
(4a) Fourier transformation is done to every a line of observation data matrix, obtain frequency-domain data matrix;
(4b) taking out the front P row of frequency-domain data matrix, as preceding paragraph difference matrix, wherein, P represents preceding paragraph difference matrix Line number, the value of P be the sum of frequency-domain data matrix row half in this interval of sum of frequency-domain data matrix row times Meaning positive integer;
(4c) taking out the rear Q row of frequency-domain data matrix, as consequent difference matrix, wherein, Q represents consequent difference matrix Line number, the value of Q is equal with the value of line number P of preceding paragraph difference matrix;
(4d) utilize preceding paragraph difference matrix and consequent difference matrix to carry out calculus of differences, obtain difference matrix;
(4e) Fourier transformation is done to each row of difference matrix, obtain spectral matrix;
(5) spectral coordinate matrix is constructed:
(5a) all elements arranging is searched in the middle of spectral matrix the row at greatest member value place, by greatest member value The row at place is as the row-coordinate of intercept;
(5b) the total line number according to spectral matrix, the total columns of spectral matrix and the Parameters Calculation set by radar system obscure Slope;
(5c) utilize slope formula, calculate intercept slope;
(5d) value of each element in spectral coordinate matrix according to the following formula, is calculated:
Wherein, [Ψ]i,jRepresent the element value of the i-th row jth row of spectral coordinate matrix, i ∈ { 1,2 ..., 2h+1}, ∈ table Showing relation belonging to, h represents the maximum detection fuzziness of the acceleration estimation according to target to be measured, j ∈ { 1,2 ..., N}, Ψ table Showing spectral coordinate matrix, K represents fuzzy slope, and κ represents intercept slope, and N represents the sum that spectral matrix arranges, and L represents spectral matrix The sum of row;
(5e) all elements of spectral coordinate matrix is arranged according to column locations, constitute spectral coordinate matrix;
(6) spectral line search method:
(6a) from spectral coordinate matrix, arbitrarily choose an element value, selected element value is sat as spectral line data is vertical Mark, using the row at selected element value place as spectral line sequence number, using the row at selected element value place as spectral line data Abscissa;
(6b) utilize search formula, calculate spectral line entry of a matrix element value;
(6c) judge whether spectral coordinate matrix has been chosen all of element value, if so, then step (6d), otherwise, Step (6a);
(6d) every data line of cumulative spectral line matrix, obtains one-dimensional spectral line data;
(6e) from all elements of one-dimensional spectral line data, the coordinate at maximum place is searched, by the coordinate at maximum place As spectral peak coordinate;
(6f) utilize fuzziness formula, calculate fuzziness;
(7) acceleration of target to be measured according to the following formula, is calculated:
Wherein, a represents the acceleration of target to be measured, and c represents the light velocity, and T represents the cycle launching signal, and M represents observation number According to the line number of matrix, n represents the line number of difference matrix, f0Representing the carrier frequency launching signal, r represents fuzziness, and L represents frequency spectrum square The sum of the row of battle array, p represents the row-coordinate of intercept;
(8) export aimed acceleration to be measured to system.
The present invention compared with prior art has the following advantages:
First, the present invention uses frequency domain phase differential method, can effectively extract the acceleration in echo-signal phase place The factor, overcoming prior art needs to build the shortcoming that sufficiently large atom could improve certainty of measurement so that the present invention has There is levels of precision high, the low advantage of computation complexity.
Second, due to the fact that employing spectral line searching method, can efficiently solve that acceleration is fuzzy to be added with maximum detection The contradiction of speed, overcomes prior art when target has high acceleration, it is impossible to the shortcoming realizing acceleration ambiguity solution, makes Obtain the present invention and there is computational accuracy height, the big advantage of interval range can be surveyed.
3rd, due to the fact that and use the method processing in two-dimensional frequency, accumulate with multicycle echo, overcome existing There is the technology shortcoming that precision is not high in the case of low signal-to-noise ratio so that the present invention has the advantage being applicable to low signal-to-noise ratio situation.
Brief description
Fig. 1 is the flow chart of the present invention;
Fig. 2 is the experiment simulation figure of the present invention.
Detailed description of the invention
The present invention will be further described below in conjunction with the accompanying drawings.
With reference to Fig. 1, the present invention to be embodied as step as follows:
Step 1. is received back to wave datum.
Gather the echo data that radar array element receives, and be stored in a matrix type in Installed System Memory.
With cycle of chirp pulse signal of launching as time interval, the echo data in the cycle is stored as A line.
Step 2. Frequency mixing processing.
Frequency mixing processing is carried out to echo data, obtains low-frequency data.
According to the chirp pulse signal design mixing function launched, carry out lower mixing and obtain low-frequency data.
Step 3. according to the following formula, carries out matched filtering to low-frequency data, obtains observing data matrix.
Y=H*X
Wherein, y represents observation data matrix, and H represents matched filtering function, and * represents convolution operation, and X represents low-frequency data.
Matched filtering function is according to the chirp pulse signal design launched, and every data line to low-frequency data matrix Do matched filtering.
Step 4. frequency domain phase difference.
Fourier transformation is done to every a line of observation data matrix, obtains frequency-domain data matrix.
Taking out the front P row of frequency-domain data matrix, as preceding paragraph difference matrix, wherein, P represents the total of preceding paragraph difference matrix row Number, the value of P is any in this interval of sum of frequency-domain data matrix row of the half of the sum of frequency-domain data matrix row Positive integer.
Taking out the rear Q row of frequency-domain data matrix, as consequent difference matrix, wherein, Q represents the total of consequent difference matrix row Number, the value of Q is equal with the value of line number P of preceding paragraph difference matrix.
Utilize preceding paragraph difference matrix and consequent difference matrix to carry out calculus of differences, obtain difference matrix.
Calculus of differences is carried out according to the following formula:
Z=Y1·conj(Y2)
Wherein, Z represents difference matrix, Y1Representing preceding paragraph difference matrix, representing dot product operation, conj represents that taking conjugation grasps Make, Y2Represent consequent difference matrix.
Realize phase difference by conjugate multiplication computing.
Fourier transformation is done to each row of difference matrix, obtains spectral matrix.
When Fourier transform is done to each row of difference matrix, Fourier transform can be selected according to the line number of difference matrix Count, such as 512 point Fourier conversion or the conversion of 1024 point Fouriers.
Step 5. constructs spectral coordinate matrix.
An all elements arranging is searched in the middle of spectral matrix the row at greatest member value place, by greatest member value place Row as the row-coordinate of intercept.
Total line number according to spectral matrix, the total columns of spectral matrix and the Parameters Calculation set by radar system are fuzzy tiltedly Rate.
Fuzzy slope is calculated according to the following formula:
Wherein, K represents fuzzy slope, and L represents the sum of the row of spectral matrix, and w represents radar sampling frequency, f0Represent and send out Penetrating the carrier frequency of signal, N represents the sum that spectral matrix arranges.
The size of radar sampling frequency refers to, staff carries out discrete adopting when using radar array element to be received back to wave datum The size of radar sampling frequency determined by during sample.
Utilize slope formula, calculate intercept slope.
Slope formula is as follows:
Wherein, κ represents intercept slope, and w represents radar sampling frequency, and p represents the value of the row-coordinate of intercept, and L represents frequency spectrum The sum of row matrix, N represents the sum that spectral matrix arranges.
According to the following formula, the value of each element in spectral coordinate matrix is calculated:
Wherein, [Ψ]i,jRepresent the element value of the i-th row jth row of spectral coordinate matrix, i ∈ { 1,2 ..., 2h+1}, ∈ table Showing relation belonging to, h represents the maximum detection fuzziness of the acceleration estimation according to target to be measured, j ∈ { 1,2 ..., N}, Ψ table Showing spectral coordinate matrix, K represents fuzzy slope, and κ represents intercept slope, and N represents the sum that spectral matrix arranges, and L represents spectral matrix The sum of row.
In embodiments of the invention, maximum detection fuzziness value is 10.
The all elements of spectral coordinate matrix is arranged according to column locations, constitutes spectral coordinate matrix.
Step 6. spectral line search method:
An element value is arbitrarily chosen from spectral coordinate matrix, using selected element value as spectral line data ordinate, Using the row at selected element value place as spectral line sequence number, using the row at selected element value place as the horizontal seat of spectral line data Mark.
Utilize search formula, calculate spectral line entry of a matrix element value.
Search formula is as follows:
Wherein, [z]α,βRepresenting the element value of the α row β row of spectral line matrix, the value of α is equal with the value of spectral line sequence number, The value of β is equal with the value of spectral line data abscissa, and z represents spectral line matrix,Represent the of spectral matrixRow χ row Element value,Value equal with the value of spectral line data ordinate, the value of χ is equal with the value of spectral line data abscissa.
Judge whether spectral coordinate matrix has been chosen all of element value, if so, then step (6d), otherwise, perform Step (6a).
Every data line of cumulative spectral line matrix, obtains one-dimensional spectral line data.
From all elements of one-dimensional spectral line data search maximum place coordinate, using the coordinate at maximum place as Spectral peak coordinate.
Utilize fuzziness formula, calculate fuzziness.
Fuzziness formula is as follows:
R=m-h-1
Wherein, r represents fuzziness, and m represents spectral peak coordinate, and h represents maximum detection fuzziness.
Step 7. according to the following formula, calculates the acceleration of target to be measured:
Wherein, a represents the acceleration of target to be measured, and c represents the light velocity, and T represents the cycle launching signal, and M represents observation number According to the line number of matrix, n represents the line number of difference matrix, f0Representing the carrier frequency launching signal, r represents fuzziness, and L represents frequency spectrum square The sum of the row of battle array, p represents the row-coordinate of intercept.
Step 8. exports aimed acceleration to be measured to system.
It is further described below in conjunction with the effect to the present invention for the emulation experiment.
1. simulated conditions:
The configuration of the operation platform of the emulation experiment of the present invention is as follows:
CPU:Intel (R) Core (TM) i7-4790CPU@3.60GHz, internal memory 8.00GB;
Operating system:64 SP1 operating systems of Windows 7 Ultimate;
Simulation software:MATLAB R(2015a).
The simulation parameter of the emulation experiment of the present invention arranges as follows:
Launching signal uses chirp pulse signal, transmission signal parameters and experiment simulation parameter to arrange as represented 1 Shown in.
Table 1 signal parameter and experiment simulation parameter list
2. emulate content:
Launch signal according to the signal parameter design radar system in table 1, build number of echoes according to the target component in table 1 According to emulating.The algorithm proposing echo data according to the present invention is processed, and obtains the measured value of aimed acceleration to be measured, And compare with emulating the aimed acceleration value setting, obtain acceleration error value.
3. analysis of simulation result:
The simulation experiment result of the present invention is as shown in Figure 2.Abscissa in Fig. 2 represents that the radially accelerated angle value of moving-target changes Scope, ordinate represents the error amount of the acceleration with emulation setting for the acceleration of calculating, and in Fig. 2, curve represents when target is accelerated Degree is successively from 340m/s2Increase 4000m/s2Error between the accekeration then recording and the accekeration of setting.
Being analyzed as follows of simulation result:
The aimed acceleration that the aimed acceleration value calculating sets with emulation is worth error amount at ± 0.3m/s2Between, When aimed acceleration is in interior change on a large scale, error amount is still at ± 0.3m/s2Between fluctuation, there is stability.
Experimental result display uses frequency domain phase difference and the 2-d spectrum spectral line aimed acceleration that calculates of search can be Solve acceleration fuzzy problem in the case of improving accuracy of detection and the little problem of scope can be surveyed, it was demonstrated that the present invention can have in target In the case of having high acceleration, it is achieved aimed acceleration measurement in high precision.

Claims (7)

1. a hypersonic target measuring acceleration method, comprises the steps:
(1) it is received back to wave datum:
Gather the echo data that radar array element receives, and be stored in a matrix type in Installed System Memory;
(2) Frequency mixing processing:
Frequency mixing processing is carried out to echo data, obtains low-frequency data;
(3) according to the following formula, matched filtering is carried out to low-frequency data, obtain observing data matrix:
Y=H*X
Wherein, y represents observation data matrix, and H represents matched filtering function, and * represents convolution operation, and X represents low-frequency data;
(4) frequency domain phase difference:
(4a) Fourier transformation is done to every a line of observation data matrix, obtain frequency-domain data matrix;
(4b) taking out the front P row of frequency-domain data matrix, as preceding paragraph difference matrix, wherein, P represents the total of preceding paragraph difference matrix row Number, the value of P is any in this interval of sum of frequency-domain data matrix row of the half of the sum of frequency-domain data matrix row Positive integer;
(4c) taking out the rear Q row of frequency-domain data matrix, as consequent difference matrix, wherein, Q represents the total of consequent difference matrix row Number, the value of Q is equal with the value of line number P of preceding paragraph difference matrix;
(4d) utilize preceding paragraph difference matrix and consequent difference matrix to carry out calculus of differences, obtain difference matrix;
(4e) Fourier transformation is done to each row of difference matrix, obtain spectral matrix;
(5) spectral coordinate matrix is constructed:
(5a) all elements arranging is searched in the middle of spectral matrix the row at greatest member value place, by greatest member value place Row as the row-coordinate of intercept;
(5b) the total line number according to spectral matrix, the total columns of spectral matrix and the Parameters Calculation set by radar system are fuzzy tiltedly Rate;
(5c) utilize slope formula, calculate intercept slope;
(5d) value of each element in spectral coordinate matrix according to the following formula, is calculated:
Wherein, [Ψ]i,jRepresenting the element value of the i-th row jth row of spectral coordinate matrix, { 1,2 ..., 2h+1}, ∈ represent genus to i ∈ In relation, h represents the maximum detection fuzziness of the acceleration estimation according to target to be measured, and { 1,2 ..., N}, Ψ represent spectrum to j ∈ Coordinates matrix, K represents fuzzy slope, and κ represents intercept slope, and N represents the sum that spectral matrix arranges, and L represents the row of spectral matrix Sum;
(5e) all elements of spectral coordinate matrix is arranged according to column locations, constitute spectral coordinate matrix;
(6) spectral line search method:
(6a) from spectral coordinate matrix, an element value is arbitrarily chosen, using selected element value as spectral line data ordinate, Using the row at selected element value place as spectral line sequence number, using the row at selected element value place as the horizontal seat of spectral line data Mark;
(6b) utilize search formula, calculate spectral line entry of a matrix element value;
(6c) judge whether spectral coordinate matrix has been chosen all of element value, if so, then step (6d), otherwise, perform Step (6a);
(6d) every data line of cumulative spectral line matrix, obtains one-dimensional spectral line data;
(6e) from all elements of one-dimensional spectral line data search maximum place coordinate, using the coordinate at maximum place as Spectral peak coordinate;
(6f) utilize fuzziness formula, calculate fuzziness;
(7) acceleration of target to be measured according to the following formula, is calculated:
Wherein, a represents the acceleration of target to be measured, and c represents the light velocity, and T represents the cycle launching signal, and M represents observation data square The line number of battle array, n represents the line number of difference matrix, f0Representing the carrier frequency launching signal, r represents fuzziness, and L represents spectral matrix The sum of row, p represents the row-coordinate of intercept;
(8) export aimed acceleration to be measured to system.
2. hypersonic target measuring acceleration method according to claim 1, it is characterised in that:Described in step (4d) Calculus of differences is carried out according to the following formula:
Z=Y1·conj(Y2)
Wherein, Z represents difference matrix, Y1Representing preceding paragraph difference matrix, representing dot product operation, conj represents and takes conjugate operation, Y2 Represent consequent difference matrix.
3. hypersonic target measuring acceleration method according to claim 1, it is characterised in that:Described in step (5b) Fuzzy slope be calculated according to the following formula:
Wherein, K represents fuzzy slope, and L represents the sum of the row of spectral matrix, and w represents radar sampling frequency, f0Represent and launch letter Number carrier frequency, N represents the sum that spectral matrix arranges.
4. hypersonic target measuring acceleration method according to claim 3, it is characterised in that:Institute in fuzzy slope formula The size of the radar sampling frequency stated refers to, when staff carries out discrete sampling when using radar array element to be received back to wave datum Determined by the size of radar sampling frequency.
5. hypersonic target measuring acceleration method according to claim 1, it is characterised in that:Described in step (5c) Slope formula is as follows:
Wherein, κ represents intercept slope, and w represents radar sampling frequency, and p represents the value of the row-coordinate of intercept, and L represents spectral matrix The sum of row, N represents the sum that spectral matrix arranges.
6. hypersonic target measuring acceleration method according to claim 1, it is characterised in that:Described in step (6b) Search formula is as follows:
Wherein, [z]α,βRepresenting the element value of the α row β row of spectral line matrix, the value of α is equal with the value of spectral line sequence number, β's Value is equal with the value of spectral line data abscissa, and z represents spectral line matrix,Represent the of spectral matrixThe unit of row χ row Element value,Value equal with the value of spectral line data ordinate, the value of χ is equal with the value of spectral line data abscissa.
7. hypersonic target measuring acceleration method according to claim 1, it is characterised in that:Described in step (6f) Fuzziness formula is as follows:
R=m-h-1
Wherein, r represents fuzziness, and m represents spectral peak coordinate, and h represents maximum detection fuzziness.
CN201610709771.7A 2016-08-23 2016-08-23 Hypersonic target measuring acceleration method Active CN106443614B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610709771.7A CN106443614B (en) 2016-08-23 2016-08-23 Hypersonic target measuring acceleration method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610709771.7A CN106443614B (en) 2016-08-23 2016-08-23 Hypersonic target measuring acceleration method

Publications (2)

Publication Number Publication Date
CN106443614A true CN106443614A (en) 2017-02-22
CN106443614B CN106443614B (en) 2018-08-21

Family

ID=58181719

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610709771.7A Active CN106443614B (en) 2016-08-23 2016-08-23 Hypersonic target measuring acceleration method

Country Status (1)

Country Link
CN (1) CN106443614B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107289951A (en) * 2017-07-31 2017-10-24 电子科技大学 A kind of Localization Approach for Indoor Mobile based on inertial navigation

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5235338A (en) * 1990-10-31 1993-08-10 Hsiao Stephen S Moving target detection through range cell migration radar
CN105548987A (en) * 2016-01-14 2016-05-04 中国人民解放军国防科学技术大学 Continuous wave radar object acceleration blind estimation method

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5235338A (en) * 1990-10-31 1993-08-10 Hsiao Stephen S Moving target detection through range cell migration radar
CN105548987A (en) * 2016-01-14 2016-05-04 中国人民解放军国防科学技术大学 Continuous wave radar object acceleration blind estimation method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
WANG GUOHONG等: "Radial acceleration estimation within one pulse echo based on Hough-ambiguity transformation", 《SCIENCE CHINA INFORMATION SCIENCES》 *
初建海 等: "脉冲雷达径向加速度提取方法研究与应用", 《弹箭与制导学报》 *
贾舒宜 等: "基于压缩感知的机动目标径向加速度估计", 《系统工程与电子技术》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107289951A (en) * 2017-07-31 2017-10-24 电子科技大学 A kind of Localization Approach for Indoor Mobile based on inertial navigation
CN107289951B (en) * 2017-07-31 2020-05-12 电子科技大学 Indoor mobile robot positioning method based on inertial navigation

Also Published As

Publication number Publication date
CN106443614B (en) 2018-08-21

Similar Documents

Publication Publication Date Title
CN103744068B (en) The moving-target detection formation method of dual pathways Continuous Wave with frequency modulation SAR system
Wang et al. Focusing spaceborne/airborne hybrid bistatic SAR data using wavenumber-domain algorithm
CN103018730B (en) Distributed sub-array wave arrival direction estimation method
Wang et al. Extending Loffeld's bistatic formula for the general bistatic SAR configuration
CN101833095B (en) Star machine united SAR (Synthetic Aperture Radar) two-dimensional frequency domain imaging method based on airspace domain expansion
CN102435763B (en) Measuring method for attitude angular velocity of spacecraft based on star sensor
Kocsis et al. Premerger localization of gravitational-wave standard sirens with LISA: Harmonic mode decomposition
CN105301590B (en) A kind of maneuvering target frequency modulation stepping inverse synthetic aperture imaging method
CN102590553B (en) Temperature compensation method for accelerometer based on wavelet noise elimination
CN105229431A (en) The level gauging that the distance with improvement is determined
CN1886094B (en) Doppler velocity detection device and ultrasonographic device using the same
CN103207380B (en) Broadband target direction finding method based on two-dimensional frequency domain sparse constraint
CN103969645A (en) Method for measuring tree heights by tomography synthetic aperture radar (SAR) based on compression multi-signal classification (CS-MUSIC)
CN103869311A (en) Real beam scanning radar super-resolution imaging method
CN103383448B (en) Clutter suppression method suitable for high pulse repetition frequency (HPRF) waveform airborne radar
CN104536000A (en) Real beam scanning radar corner super-resolution method
Luo et al. Micro-Doppler feature extraction for wideband imaging radar based on complex image orthogonal matching pursuit decomposition
CN105319389B (en) A kind of high precision wide range ultrasound wind system and method
CN103217162B (en) Adopt the pulsar pile-up pulse profile time delay measurement method of rarefaction representation
CN101907704A (en) Method for evaluating simulation imaging of multi-mode synthetic aperture radar
CN103616687B (en) The fitting of a polynomial ISAR envelope alignment method that piecewise linearity is estimated
CN104515971A (en) Airborne single-station passive positioning method for multiple broadband targets
CN104502898B (en) The maneuvering target method for parameter estimation that modified R FT and amendment MDCFT are combined
CN103675759B (en) A kind of motor-driven weak target detection method of Fourier Transform of Fractional Order of improvement
CN102495393B (en) Compressive sensing radar imaging algorithm based on subspace tracking

Legal Events

Date Code Title Description
PB01 Publication
C06 Publication
SE01 Entry into force of request for substantive examination
C10 Entry into substantive examination
GR01 Patent grant
GR01 Patent grant