CN113391284A - Temporary high-speed target detection method based on long-time accumulation - Google Patents
Temporary high-speed target detection method based on long-time accumulation Download PDFInfo
- Publication number
- CN113391284A CN113391284A CN202110568283.XA CN202110568283A CN113391284A CN 113391284 A CN113391284 A CN 113391284A CN 202110568283 A CN202110568283 A CN 202110568283A CN 113391284 A CN113391284 A CN 113391284A
- Authority
- CN
- China
- Prior art keywords
- speed
- target
- echo data
- acceleration
- segment
- 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.)
- Pending
Links
- 238000009825 accumulation Methods 0.000 title claims abstract description 92
- 238000001514 detection method Methods 0.000 title claims abstract description 22
- 230000001427 coherent effect Effects 0.000 claims abstract description 76
- 238000000034 method Methods 0.000 claims abstract description 36
- 230000033001 locomotion Effects 0.000 claims abstract description 24
- 238000012545 processing Methods 0.000 claims abstract description 14
- 238000007906 compression Methods 0.000 claims abstract description 11
- 230000011218 segmentation Effects 0.000 claims abstract description 11
- 230000006835 compression Effects 0.000 claims abstract description 8
- 230000001133 acceleration Effects 0.000 claims description 56
- 238000012937 correction Methods 0.000 claims description 9
- 238000010606 normalization Methods 0.000 claims description 9
- 239000011159 matrix material Substances 0.000 claims description 7
- 230000008859 change Effects 0.000 claims description 6
- 238000013499 data model Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 230000035485 pulse pressure Effects 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 3
- 239000007983 Tris buffer Substances 0.000 claims description 2
- 238000010276 construction Methods 0.000 claims description 2
- 230000000717 retained effect Effects 0.000 claims description 2
- 239000004576 sand Substances 0.000 claims description 2
- 239000000126 substance Substances 0.000 claims description 2
- 238000004364 calculation method Methods 0.000 abstract description 8
- 238000005516 engineering process Methods 0.000 description 7
- 238000004088 simulation Methods 0.000 description 6
- 238000004422 calculation algorithm Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000007123 defense Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000002592 echocardiography Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/415—Identification of targets based on measurements of movement associated with the target
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention belongs to the technical field of radar signal processing, and particularly discloses a temporary high-speed target detection method based on long-time accumulation, which comprises the steps of firstly segmenting echo signals after pulse compression according to pulse number, and compensating the distance walk and Doppler spread of echo signal envelopes in each segment; then carrying out coherent accumulation in each section on the compensated result in each section; finally, envelope movement and non-coherent accumulation between segments are carried out on all echo signals, so that the energy of the echo signals can be effectively accumulated. By adopting the long-time accumulation method of time segmentation, intra-segment coherent accumulation and inter-segment non-coherent accumulation, the problem of the calculation amount of the long-time coherent accumulation is solved, and the problem of the phase coherence of echo signals is deteriorated is also solved; the detection performance is improved, and the engineering implementation is easy.
Description
Technical Field
The invention relates to the technical field of radar signal processing, in particular to a method for detecting a temporary altitude high-speed target based on long-time accumulation, which can be used for improving accumulation gain, reducing calculation amount and facilitating engineering realization.
Background
With the development of aerospace technology, hypersonic aircrafts are concerned by military countries with extremely attractive military application prospects. The novel technology integrates the novel technologies of a plurality of disciplines in the aerospace field, represents the research and development direction of the aerospace field in the future, and is regarded as another important technical field behind stealth technology in the military. The hypersonic aircraft generally flies in 20 km-100 km near space, has the characteristics of long combat distance, high flying speed, strong maneuverability and the like, can penetrate through radar beams in extremely short time, breaks through the existing air defense system, and brings great threat to the air safety of the country. The method has important significance in the research of high-speed and high-maneuvering target detection technology in the face of various defense penetration means of the hypersonic aircraft in the near space.
Generally, observation time can be increased, a long-time accumulation technology is adopted to improve the output signal-to-noise ratio of the target, and time is used for exchanging energy, so that the detection performance of the radar on the target is improved. However, in the long-time accumulation process, due to the high-speed and high-mobility motion characteristics of a high-speed target in an adjacent space, the phenomena of range migration and Doppler spread occur, so that the traditional coherent accumulation effect is seriously deteriorated. The plasma sheath is generated by air ionization caused by considering the high-speed movement of the target in the atmospheric layer and air friction, and the coherence of the echo signal is deteriorated. If the long-time coherent accumulation is still carried out, the result is deteriorated; meanwhile, from the perspective of hardware realization, long-time coherent accumulation has high requirements on equipment quantity and high cost. Therefore, the method has urgent practical significance for researching the effective and easily-implemented long-time accumulation algorithm and detecting the high-speed target in the adjacent space.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide a temporary high-speed target detection method based on long-time accumulation, which adopts a long-time accumulation method of time segmentation, intra-segment coherent accumulation and inter-segment non-coherent accumulation, thereby solving the problem of the calculation amount of the long-time coherent accumulation and the problem of the phase difference deterioration of echo signals; the detection performance is improved, and the engineering implementation is easy.
The technical principle of the invention is as follows: firstly, segmenting echo signals after pulse compression according to pulse number, and compensating distance walk and Doppler expansion of the envelope of the echo signals in each segment; then carrying out coherent accumulation in each section on the compensated result in each section; finally, envelope movement and non-coherent accumulation between segments are carried out on all echo signals, so that the energy of the echo signals can be effectively accumulated.
In order to achieve the purpose, the invention is realized by adopting the following technical scheme.
A temporary altitude high-speed target detection method based on long-time accumulation comprises the following steps:
Wherein m is 0,1,., N-1, N represents the total number of accumulated pulses; t is tkFor a fast time, tmIs a slow time;
WhereinEach Q pulse repetition intervals as a coherent processing time period, Q being an integer power of 2, mi＝(i-1)×Q，(i-1)×Q+1，...，i×Q-1，N＝M×Q；
Step 3, constructing the traversal interval and step length of the search speed, and according to each search speed vsConstructing corresponding phase compensation factors to form a compensation matrix Hv(vs) And is combined with the first section echo data
Multiplying to obtain compensated first section echo data, and estimating the target motion speed; forming an optimal compensation matrix according to the target motion speed estimation value, respectively compensating all echo data segments to obtain M echo data segments after phase compensation, converting the M echo data segments after phase compensation into a distance time domain through IFFT to obtain a time domain signal after phase compensation
Step 4, estimating Doppler frequency modulation of the time domain signals by using a line-off frequency modulation method, namely estimating target acceleration, constructing a Doppler compensation item according to the target acceleration estimation value, and compensating all phase-compensated time domain signals to realize Doppler spread compensation;
step 6, determining distance unit differences and Doppler channel differences among different echo data, constructing a distance direction compensation factor by adopting the inter-segment distance unit differences, and performing distance direction compensation on the M echo data segments after coherent accumulation to obtain M echo data segments after inter-segment envelope alignment;
step 7, carrying out normalization processing on the M echo data segments after the envelope alignment between the segments to obtain M echo data segments after normalization; by utilizing the inter-segment Doppler channel difference determined in the step 6, extracting the data of the Doppler channel corresponding to each segment of data in the M normalized echo data segments, taking a modulus value, and then adding the modulus values to realize inter-segment non-coherent accumulation so as to obtain the echo data after the inter-segment non-coherent accumulation; and carrying out target detection on the echo data after the inter-segment non-coherent accumulation.
Compared with the prior art, the invention has the beneficial effects that:
(1) for very mobile targets such as airplanes, long-term coherent accumulation techniques are limited. The long-time coherent accumulation technology assumes that the motion of the target is stable, and the radial speed of the target remains unchanged, but during long-time detection, the track and the speed of the motion of the target are usually changed, and coherent accumulation cannot be realized. The invention adopts the long-time accumulation method of time segmentation, intra-segment coherent accumulation and inter-segment non-coherent accumulation, thereby not only solving the problem of the calculation amount of the long-time coherent accumulation, but also solving the problem of the phase difference variation of echo signals; meanwhile, when the intra-segment distance walk correction and Doppler spread compensation are carried out, the traversal search quantity of the target speed and the target acceleration can be reduced, so that the calculation quantity of the algorithm is reduced, and the engineering implementation is easy.
(2) When the MTD detection is performed for all echoes over a long period of time, even if the target does not move around, the energy is dispersed among a plurality of velocity elements due to the change in velocity, because the velocity (doppler) elements are too finely divided. The invention adopts the methods of time segmentation, intra-segment coherent accumulation and inter-segment non-coherent accumulation, and can prevent the speed division of the target. After the signals are segmented, the coherent accumulated pulse number in each segment is small, the speed unit is coarse, and when the speed change of the target is not large, the target still falls into one speed unit; the module values of the coherent accumulation results of data of various batches in a plurality of time periods are overlapped, non-coherent accumulation is realized, and velocity splitting can not occur.
Drawings
The invention is described in further detail below with reference to the figures and specific embodiments.
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2(a) is a contour result graph of a first echo signal after pulse compression according to the present invention;
FIG. 2(b) is a result graph of a contour line of a first echo signal after distance walk correction in the present invention;
FIG. 3(a) is a diagram showing the result of coherent accumulation after distance walk correction of the first echo signal in the present invention;
FIG. 3(b) is a diagram showing the result of coherent accumulation of the first echo signal after Doppler spread compensation in the present invention;
FIG. 4(a) is a diagram showing the results of the first, fourth and eighth peak positions of the echo signal after coherent accumulation in the segment according to the present invention;
FIG. 4(b) is a diagram showing the result of the peak positions of the first, fourth and eighth segments after the echo signal is subjected to the envelope shift between the segments;
FIG. 5 is a diagram showing the result of echo signal after non-coherent accumulation between segments;
FIG. 6 is a graph showing the comparison between the algorithm calculation amount of the method of the present invention and the conventional long-term coherent accumulation method and the trend of the accumulated pulse number.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to examples, but it will be understood by those skilled in the art that the following examples are only illustrative of the present invention and should not be construed as limiting the scope of the present invention.
Referring to fig. 1, the invention provides a temporary air high-speed target detection method based on long-time accumulation, which comprises the following steps:
the method specifically comprises the following steps:
1.1, establishing a motion model of a high-speed maneuvering target: for moving objects, the distance between the object and the radar is over a slow time tmTime-varying, and can be represented as tmThe polynomial function of (2) on which taylor series expansion is performed can be expressed as:
wherein P is the order of the target motion, alphapIs the motion parameter of the p-th order. In the present invention, the first four terms of taylor series are retained, i.e. P is taken to be 3, the above equation can be simplified as:
in the formula, R (t)m) Representing the distance, R, between the target and the radar in the m-th pulse repetition period0Represents the initial slope distance of the target, v is the target radial velocity, and a is the target radial acceleration.
1.2, constructing a radar echo data model under a long-time observation condition:
under the condition of a narrow-band point target, constructing a baseband echo signal model received by a radar as follows:
wherein σ0Which represents the reflection coefficient of the object and,
as a function of a rectangular window, TpIs the rectangular pulse width, B is the modulation bandwidth,
to the frequency modulation, fcIs carrier frequency, j is an imaginary number unit, and c is the propagation speed of electromagnetic waves in the air; let tm＝mTr(m-0, 1.., N-1) denotes a slow time, TrFor the pulse repetition interval, N is the total number of accumulated pulses.
The time domain expression of the matched filter is
The frequency-slow time domain expression of the echo signal after pulse pressure is as follows:
wherein A is0Is the signal amplitude after pulse compression.
For echo data SP(f，tm) When segmentation is carried out, the real-time processing capacity of actual hardware equipment and the searching precision of the speed and the acceleration in the steps 3 and 4 are considered; while the number of pulses Q in each segment satisfies an integer power of 2 to facilitate fast fourier transform FFT.
Step 3, constructing the traversal interval and step length of the search speed, and according to each search speed vsConstructing corresponding phase compensation factors to form a compensation matrix Hv(vs) And is combined with the first section echo data
Multiplying to obtain compensated first section echo data, and estimating the target motion speed; forming an optimal complement based on the target motion velocity estimateCompensating the matrix, respectively compensating all the echo data segments to obtain M echo data segments after phase compensation, transforming the M echo data segments after phase compensation to a distance time domain through IFFT to obtain time domain signals after phase compensation
Firstly, designing a method for estimating the movement speed of a target according to radar system parameters and prior information of the target, wherein the method comprises the following steps:
3.1, determining the maximum speed v of search traversal according to the prior information of the target (the maximum possible flying speed of the detected target)max；
3.2, determining the maximum search traversal interval delta v of the speed according to the radar system parameters, and when the speed v is searched during the speed searchsWhen the speed is matched with the target real speed v, the following relation is provided:
|v-vs|≤Δvs/2
wherein, Δ vsThe interval is searched for a velocity. When searching for velocity vsWhen the distance between the first echo pulse peak and the last echo pulse peak is matched with the real speed v of the target, after the distance walk correction is carried out by using a frequency domain phase compensation method, the distance between the first echo pulse peak and the last echo pulse peak cannot exceed a distance unit, namely the following relation is satisfied:
wherein Q represents the number of pulses in each segment after segmentation, c is the speed of light, B is the signal bandwidth, TrIs a pulse repetition period.
Because the difference between the searched speed and the real speed of the target is delta vsAnd/2, after compensation, the distance walk caused by the residual speed of the k-th section of echo signal is as follows:
wherein R isresc/2B, distance resolution unit.
Further, in order to ensure the distance positioning between the segments, the search interval needs to be reduced by M-1 times, and then the maximum search interval of the speed is set as
Δv＝c/(QBTr)/(M-1)
3.3, determining the search traversal range of the speed according to steps 3.1 and 3.2 as follows: [ -v ]max，-Δv]∪[Δv，vmax]
3.4, according to the search speed vsConstructing a phase compensation factor:
Hv(vs)＝exp(j2πf·2vsm1Tr/c)
wherein m is1＝0，1，...，Q-1；
Using a phase compensation factor Hv(vs) For the first section echo data
Performing frequency domain compensation, and performing Inverse Fast Fourier Transform (IFFT) along the fast time frequency to obtain compensated (t)k-tm) First segment echo data of the domain:
where sin c (x) ═ sin (pi x)/(pi x) denotes the Sa function, and λ ═ c/fcIs the radar wavelength.
Neglecting the distance walk caused by acceleration, then when vsWhen the search speed is equal to the target real speed, the peak value of the envelope of the first section echo signal is in the same distance unit, and the target speed estimated value is obtained according to the peak value
Based on the target velocity estimate
Constructing an optimal compensation matrix
Performing frequency domain compensation on all echo data segments, and performing IFFT along the fast time frequency to obtain a time domain signal after phase compensation:
wherein i is 1, 2., M,
representing the compensated time domain signal of the i-th segment.
Step 4, estimating Doppler frequency modulation of the time domain signals by using a line-off frequency modulation method, namely estimating target acceleration, constructing a Doppler compensation item according to the target acceleration estimation value, and compensating all phase-compensated time domain signals to realize Doppler spread compensation;
the process is similar to step 3, and specifically comprises the following steps:
4.1, determining the maximum acceleration a of the search traversal according to the prior information of the target (the maximum possible flight acceleration of the detected target)max；
4.2, determining the maximum search traversal interval delta a of the acceleration according to the radar system parameters, and when the searched acceleration asWhen the acceleration a of the target is matched with the real acceleration a of the target, the following relation is given
|a-as|≤Δas/2
Wherein, Δ asThe interval is searched for the acceleration. Therefore, when the echo signal is compensated by the searched acceleration, the velocity change caused by the residual acceleration should not exceed one Doppler unit, that is
Namely, it is
Δas≤λ/(QTr)2
Wherein Q represents the number of pulses in each segment after segmentation, λ is the wavelength, frIs the pulse repetition frequency. When the acceleration searching is carried out by using the searching mode, the maximum difference value between the searched acceleration and the real acceleration of the target is delta as/2. The velocity change caused by the target residual acceleration after compensation is as follows:
where k denotes the kth signal after segmentation, vresIndicating a doppler resolution cell.
That is, the doppler units of the targets of each segment obtained after the acceleration compensation is searched by using the above search method are different, and in order to ensure that the condition does not occur, the search interval is reduced by M-1 times, wherein M is the number of the segments finally divided. The maximum search interval for acceleration is then:
Δas＝λ/(QTr)2/(M-1)
4.3, determining the search traversal range of the acceleration according to the steps 4.1 and 4.2 as follows: [ -a [ ]max，-Δa]∪[Δa，amax]；
4.4, according to the search acceleration asObtaining the search modulation frequency gammas＝-2asLambda, form compensation factor
And for the first section echo data
And (3) carrying out frequency domain compensation, and then searching out the maximum energy peak value through the following formula so as to calculate the optimal frequency modulation rate:
wherein the content of the first and second substances,
and representing a slow time dimension signal corresponding to the distance unit where the target is located.
When in use
Is equal to
True frequency γ of modulationaAt-2 a/λ, an energy peak occurs, and the frequency modulation rate corresponding to the peak is the true frequency modulation rate.
Then, a compensation factor constructed using the true tuning frequency is used
Compensating all echo data segments after distance walk correction to obtain:
wherein i is 1, 2., M,
representing the compensated echo of the ith segment. From the equation, it can be seen that the temporal high-order term corresponding to the acceleration in the signal is eliminated, and the doppler spread is compensated.
step 6, determining distance unit differences and Doppler channel differences among different echo data, constructing a distance direction compensation factor by adopting the inter-segment distance unit differences, and performing distance direction compensation on the M echo data segments after coherent accumulation to obtain M echo data segments after inter-segment envelope alignment;
6.1 from step 4
As can be seen from the above expression, the difference in the range unit between the peak positions of the ith echo data and the first echo data is (i-1) vQTr(ii) a After coherent accumulation in the segment, the Doppler channel difference at the peak position between the ith segment of echo data and the first segment of echo data is (i-1) aQTr(ii) a The two differences are used to realize envelope movement and non-coherent accumulation between segments in subsequent steps.
6.2, using the velocity estimate searched in step 3
Construction of the phase Compensation factor exp (j2 π ft'i) Wherein
Representing the time delay difference of the ith section signal and the first section signal; and 5, performing fast time-dimensional FFT on the echo signals after coherent accumulation in the step 5, compensating in a distance frequency domain, and performing fast time-dimensional IFFT to obtain shifted signals:
at this time, the peak position of the signal in each segment is shifted to
And then, non-coherent accumulation between segments can be carried out, so that the energy of all echo signals is accumulated, and the subsequent target detection is facilitated.
Step 7, carrying out normalization processing on the M echo data segments after the envelope alignment between the segments to obtain M echo data segments after normalization; by utilizing the inter-segment Doppler channel difference determined in the step 6, extracting the data of the Doppler channel corresponding to each segment of data in the M normalized echo data segments, taking a modulus value, and then adding the modulus values to realize inter-segment non-coherent accumulation so as to obtain the echo data after the inter-segment non-coherent accumulation; and carrying out target detection on the echo data after the inter-segment non-coherent accumulation.
7.1, for the shifted signal obtained in step 6
Carrying out normalization operation to obtain
Initializing a Doppler channel serial number j equal to 1;
7.2, extracting the data of the corresponding Doppler channel in each section
And taking the modulus to add to obtain the data of the jth Doppler channel which is not coherent and accumulated, namely:
wherein d isi，j＝j+(i-1)aQTrIndicating a Doppler channel corresponding to the ith section of data;
7.3, if j is less than Q, making j equal to j +1, and returning to the step 7.2; otherwise, obtaining the non-coherent accumulation result y between the segmentsout(tk，tl) Wherein t isl＝1，2，...，Q；
7.4, for the accumulated results yout(tk，tl) And carrying out constant false alarm detection to obtain target information.
Simulation experiment
The effect of the present invention is further explained by simulation experiments.
1. Simulation conditions
Assuming that a radar transmitting signal is a linear frequency modulation signal, the carrier frequency of the signal is 1GHz, the bandwidth of the signal is 1MHz, the sampling rate is 2MHz, the pulse width of the transmitting signal is 2ms, the pulse repetition period is 8.4ms, the number of accumulated pulses is 256, the initial speed of a target is 6800m/s, and the acceleration is 60m/s2The initial distance between the radar and the target is 150Km,the signal-to-noise ratio is-20 dB.
2. Emulated content
3. Analysis of simulation results
As can be seen from fig. 2(a) and 2(b), although the number of accumulated pulses per group is only 32, distance walk occurs in the echo signal due to the relatively high moving speed of the target; after speed compensation, echo signals of different pulses are corrected to the same distance unit, and distance walk between the pulses is corrected.
As can be seen from fig. 3(a) and 3(b), since the target has acceleration, when the echo is directly subjected to coherent accumulation, the doppler spread of the distance unit where the target is located is severe, the energy of the echo signal cannot be effectively accumulated, and energy loss exists, which is not favorable for subsequent target detection, so that certain means are required to compensate the echo signal, and the signal-to-noise ratio during target detection is ensured; after acceleration compensation, coherent accumulation is carried out, the energy of the echo signal is effectively accumulated in a Doppler unit, and then the inter-segment processing can be carried out continuously.
As can be seen from fig. 4(a) and 4(b), after a series of processing on signals in the segments, the energy of the target can be effectively accumulated, but the distance difference between the segments still remains to be solved; after the frequency domain envelope displacement, the peak position of each segment is in the same distance unit, and the distance difference between the segments is effectively compensated.
As can be seen from FIG. 5, after the inter-segment non-coherent accumulation, the target energy is effectively accumulated, which is beneficial to the subsequent target detection and verifies the effectiveness of the method.
As can be seen from fig. 6, as the number of accumulated pulses increases, the number of times of searching in the conventional long-time coherent accumulation method increases rapidly, which means that the calculation amount of the algorithm increases sharply, while the method provided by the present invention has a slow growth trend, and the variation of the calculation amount is small in comparison, which is more beneficial to engineering implementation and real-time processing.
Although the present invention has been described in detail in this specification with reference to specific embodiments and illustrative embodiments, it will be apparent to those skilled in the art that modifications and improvements can be made thereto based on the present invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.
Claims (9)
1. A temporary altitude high-speed target detection method based on long-time accumulation is characterized by comprising the following steps:
step 1, establishing a high-speed maneuvering target motion model, constructing a radar echo data model under a long-time observation condition, and sequentially changing original echo data downFrequency and low-pass filtering to obtain the baseband echo data s received by the radarr(tk,tm) (ii) a Then, the baseband echo data s is filtered by a matched filterr(tk,tm) Performing pulse compression to obtain echo data S of frequency-slow time domain after pulse compressionP(f,tm)；
Wherein m is 0,1,., N-1, N represents the total number of accumulated pulses; t is tkFor a fast time, tmIs a slow time;
step 2, according to the slow time dimension, the echo data S of the frequency-slow time domain after pulse pressure is processedP(f,tm) Division into M echo data segments
Wherein each Q pulse repetition intervals are taken as a coherent processing time period, Q is an integer power of 2, mi＝(i-1)×Q,(i-1)×Q+1,...,i×Q-1，N＝M×Q；
Step 3, constructing the traversal interval and step length of the search speed, and according to each search speed vsConstructing corresponding phase compensation factors to form a compensation matrix Hv(vs) And is combined with the first section echo data
Multiplying to obtain compensated first section echo data, and estimating the target motion speed; forming an optimal compensation matrix according to the target motion speed estimation value, respectively compensating all echo data segments to obtain M echo data segments after phase compensation, converting the M echo data segments after phase compensation into a distance time domain through IFFT to obtain a time domain signal after phase compensation
Step 4, estimating Doppler frequency modulation of the time domain signals by using a line-off frequency modulation method, namely estimating target acceleration, constructing a Doppler compensation item according to the target acceleration estimation value, and compensating all phase-compensated time domain signals to realize Doppler spread compensation;
step 5, performing fast Fourier transform of Q points on each distance unit of the M echo data segments compensated in the step 4, respectively gathering energy in each echo data segment in a distance unit and a Doppler unit, realizing coherent accumulation in the data segments, and obtaining the M echo data segments after coherent accumulation;
step 6, determining distance unit differences and Doppler channel differences among different echo data, constructing a distance direction compensation factor by adopting the inter-segment distance unit differences, and performing distance direction compensation on the M echo data segments after coherent accumulation to obtain M echo data segments after inter-segment envelope alignment;
step 7, carrying out normalization processing on the M echo data segments after the envelope alignment between the segments to obtain M echo data segments after normalization; by utilizing the inter-segment Doppler channel difference determined in the step 6, extracting the data of the Doppler channel corresponding to each segment of data in the M normalized echo data segments, taking a modulus value, and then adding the modulus values to realize inter-segment non-coherent accumulation so as to obtain the echo data after the inter-segment non-coherent accumulation; and carrying out target detection on the echo data after the inter-segment non-coherent accumulation.
2. The method for detecting the temporary airspace high-speed target based on the long-time accumulation according to claim 1, wherein in step 1, the motion model of the high-speed maneuvering target is as follows:
for moving objects, the distance between the object and the radar is over a slow time tmTime-varying, and can be represented as tmThe polynomial function of (2) is expressed by Taylor series expansion:
wherein P is the order of the target motion, alphapIs a motion parameter of the p-th order; if the first four terms of the taylor series are retained, i.e. P is taken to be 3, the above equation can be simplified as:
in the formula, R (t)m) Representing the distance, R, between the target and the radar in the m-th pulse repetition period0Representing the initial slope distance of the target, v is the radial speed of the target, and a is the radial acceleration of the target;
the baseband echo data is:
wherein σ0Which represents the reflection coefficient of the object and,
as a function of a rectangular window, TpIs the rectangular pulse width, B is the modulation bandwidth,
to the frequency modulation, fcIs carrier frequency, j is an imaginary number unit, and c is the propagation speed of electromagnetic waves in the air; let tm＝mTr(m-0, 1.., N-1) denotes a slow time, TrFor the pulse repetition interval, N is the total number of accumulated pulses.
3. The method for detecting the temporary airspace high-speed target based on the long-time accumulation according to claim 1, wherein in step 3, the estimation process of the target movement speed is as follows:
3.1, taking the maximum possible flying speed of the detected target as the maximum speed v of search traversalmax；
3.2, determining the maximum search traversal interval delta v of the speed according to the radar system parameters, and when the speed search is carried out, searching the speed vsWhen the speed is matched with the target real speed v, the following relation is provided:
|v-vs|≤△vs/2
wherein, Δ vsSearching for an interval for a velocity;
when searching for velocity vsWhen the distance between the first echo pulse peak and the last echo pulse peak is matched with the real speed v of the target, after the distance walk correction is carried out by using frequency domain phase compensation, the distance between the first echo pulse peak and the last echo pulse peak cannot exceed a distance unit, namely the following relation is satisfied:
wherein Q represents the number of pulses in each segment after segmentation, c is the speed of light, B is the signal bandwidth, TrIs a pulse repetition period;
because the difference between the searched speed and the real speed of the target is delta vsAnd/2, after compensation, the distance walk caused by the residual speed of the k-th section of echo signal is as follows:
wherein R isresc/2B, which is a distance resolution unit;
further, in order to ensure the distance positioning between the segments, the search interval needs to be reduced by M-1 times, and then the maximum search interval of the speed is set as
△v＝c/(QBTr)/(M-1)；
3.3, determining the search traversal range of the speed according to steps 3.1 and 3.2 as follows: [ -v ]max,-△v]∪[△v,vmax]；
3.4, according to the search speed vsConstructing a phase compensation factor:
Hv(vs)＝exp(j2πf·2vsm1Tr/c)
wherein m is1＝0,1,...,Q-1；
Using a phase compensation factor Hv(vs) For the first section echo data
Performing frequency domain compensation, and performing inverse fast Fourier transform along the fast time frequency to obtain compensated (t)k-tm) First segment echo data of the domain:
where sinc (x) sin (pi x)/(pi x) represents a Sa function, and λ c/fcIs the radar wavelength;
neglecting the distance walk caused by acceleration, then when vsWhen the search speed is equal to the target real speed, the peak value of the envelope of the first section echo signal is in the same distance unit, and the target speed estimated value is obtained according to the peak value
4. The method for detecting the temporary airspace high-speed target based on the long-time accumulation according to claim 3, wherein the time domain signal after the phase compensation is:
wherein, i is 1, 2.. times, M,
represents the compensated time domain signal of the i-th segment, A3To represent
The signal amplitude of (c).
5. The method for detecting the temporary airspace high-speed target based on the long-time accumulation according to claim 1, wherein the estimation of the doppler modulation frequency of the time domain signal by using the dechirp method comprises the following specific processes:
4.1, determining the maximum possible flight acceleration of the detected target as the maximum acceleration a of search traversalmax；
4.2, determining the maximum search traversal interval delta a of the acceleration according to the radar system parameters, and determining the maximum search traversal interval delta a of the acceleration when the searched acceleration asWhen the acceleration a of the target is matched with the real acceleration a of the target, the following relation is provided:
|a-as|≤△as/2
wherein, Δ asSearching for an interval for acceleration;
when the echo signal is compensated by the searched acceleration, the velocity change caused by the residual acceleration should not exceed one Doppler unit, i.e.
Namely, it is
△as≤λ/(QTr)2
Wherein Q represents the number of pulses in each segment after segmentation, λ is the wavelength, frIs the pulse repetition frequency; when the acceleration searching is carried out by using the searching mode, the maximum difference value between the searched acceleration and the real acceleration of the target is delta as2; the velocity change caused by the target residual acceleration after compensation is as follows:
where k denotes the kth signal after segmentation, vresRepresents a doppler resolution cell;
in order to avoid that the Doppler units where the targets of each section are located are different after the acceleration compensation is obtained through searching, the searching interval is reduced by M-1 times, wherein M is the number of the sections which are finally divided, and then the maximum searching interval of the acceleration is as follows:
△as＝λ/(QTr)2/(M-1)
4.3, determining the search traversal range of the acceleration according to the steps 4.1 and 4.2 as follows: [ -a [ ]max,-△a]∪[△a,amax]；
4.4, according to the search acceleration asObtaining the search modulation frequency gammas＝-2asLambda, form compensation factor
And for the first section echo data
And (3) carrying out frequency domain compensation, and then searching out the maximum energy peak value through the following formula so as to calculate the optimal frequency modulation rate:
wherein, | - | represents a modulus value,
and representing a slow time dimension signal corresponding to the distance unit where the target is located.
6. The method for detecting the temporary airspace high-speed target based on the long-time accumulation according to claim 5, wherein the doppler compensation term is constructed according to the target acceleration estimation value, and the time domain signals after all phase compensation are compensated, specifically:
wherein, i is 1, 2.. times, M,
representing the i-th phase-compensated time-domain signal, A4To represent
The signal amplitude of (c).
7. The method for detecting the temporary airspace high-speed target based on the long-time accumulation according to claim 6, wherein the determining the distance unit difference and the Doppler channel difference between different echo data comprises the following specific processes:
from
As can be seen from the above expression, the difference in the range unit between the peak positions of the ith echo data and the first echo data is (i-1) vQTr(ii) a After coherent accumulation in the segment, the Doppler channel difference at the peak position between the ith segment of echo data and the first segment of echo data is (i-1) aQTr。
8. The long-time accumulation based sky-approaching high-speed target detection method according to claim 1, wherein the distance direction compensation factor is constructed by adopting inter-segment distance unit difference, and distance direction compensation is performed on M echo data segments after coherent accumulation, specifically:
using the velocity estimate searched in step 3
Construction of the phase Compensation factor exp (j2 π ft'i) Wherein, the time delay difference of the ith segment signal and the first segment signal is represented; and (3) performing fast time-dimensional FFT on the M echo data segments after the coherent accumulation in the step (5), compensating in a distance frequency domain, and performing fast time-dimensional IFFT to obtain echo data segments after the inter-segment envelopes are aligned:
wherein the content of the first and second substances,
representing the i-th phase compensated time domain signal,
c is the propagation speed of the electromagnetic wave in the air; t isrIs the pulse repetition interval.
9. The method for detecting the temporary airspace high-speed target based on the long-time accumulation according to claim 1, wherein the non-coherent accumulation between the segments is specifically as follows:
7.1, for the shifted signal obtained in step 6
Carrying out normalization operation to obtain
Initializing a Doppler channel serial number j equal to 1;
7.2, extracting the data of the corresponding Doppler channel in each section
And taking the modulus to add to obtain the data of the jth Doppler channel which is not coherent and accumulated, namely:
wherein d isi,j＝j+(i-1)aQTrIndicating a Doppler channel corresponding to the ith section of data;
7.3 if j<Q, let j equal j +1, return to step 7.2; otherwise, obtaining the non-coherent accumulation result y between the segmentsout(tk,tl) Wherein t isl＝1,2,…,Q。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110568283.XA CN113391284A (en) | 2021-05-25 | 2021-05-25 | Temporary high-speed target detection method based on long-time accumulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110568283.XA CN113391284A (en) | 2021-05-25 | 2021-05-25 | Temporary high-speed target detection method based on long-time accumulation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113391284A true CN113391284A (en) | 2021-09-14 |
Family
ID=77618851
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110568283.XA Pending CN113391284A (en) | 2021-05-25 | 2021-05-25 | Temporary high-speed target detection method based on long-time accumulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113391284A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114371460A (en) * | 2022-01-24 | 2022-04-19 | 电子科技大学 | Airborne radar sea surface moving target energy accumulation and sea clutter suppression method |
| CN114415122A (en) * | 2022-01-27 | 2022-04-29 | 电子科技大学 | High-speed target accumulation detection method based on frequency domain segmentation processing |
| CN116106852A (en) * | 2023-04-12 | 2023-05-12 | 中国人民解放军63921部队 | Method and device for determining airborne main clutter channel and electronic equipment |
-
2021
- 2021-05-25 CN CN202110568283.XA patent/CN113391284A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114371460A (en) * | 2022-01-24 | 2022-04-19 | 电子科技大学 | Airborne radar sea surface moving target energy accumulation and sea clutter suppression method |
| CN114415122A (en) * | 2022-01-27 | 2022-04-29 | 电子科技大学 | High-speed target accumulation detection method based on frequency domain segmentation processing |
| CN116106852A (en) * | 2023-04-12 | 2023-05-12 | 中国人民解放军63921部队 | Method and device for determining airborne main clutter channel and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113391284A (en) | Temporary high-speed target detection method based on long-time accumulation | |
| CN111736128B (en) | Phase-coherent accumulation method based on SKT-SIAF-MSCFT | |
| Li et al. | Range migration compensation and Doppler ambiguity resolution by keystone transform | |
| CN108398676B (en) | External radiation source radar weak moving target detection method | |
| CN104076351B (en) | Phase-coherent accumulation detection method for high-speed high maneuvering target | |
| CN103323829B (en) | Based on the radar moving targets long-time phase-coherent accumulation detection method of Radon-fractional order ambiguity function | |
| CN107450055B (en) | High-speed maneuvering target detection method based on discrete linear frequency modulation Fourier transform | |
| CN106443671A (en) | SAR radar moving target detecting and imaging method based on FM continuous wave | |
| CN108344982B (en) | Small unmanned aerial vehicle target radar detection method based on long-time coherent accumulation | |
| CN111123214B (en) | Polynomial rotation-polynomial Fourier transform high-speed high-maneuvering target detection method | |
| CN109655802B (en) | Multi-target particle swarm long-time accumulation detection method based on CLEAN algorithm | |
| CN108535724B (en) | Moving target focusing method based on keystone transformation and integral quadratic function | |
| CN109633622B (en) | Radar maneuvering target cross-unit accumulation method based on time reversal second-order Keystone transformation | |
| CN105445707A (en) | Clutter inhibition method of airborne external radiation source radar | |
| CN110824439B (en) | Radar target rapid long-time coherent accumulation method | |
| Jin et al. | Coherent detection and parameter estimation for radar high-speed maneuvering target based on FAF–LVD | |
| Sun et al. | A fast approach for detection and parameter estimation of maneuvering target with complex motions in coherent radar system | |
| CN112327285B (en) | Radar target detection method based on mixed generalized Reden Fourier transform | |
| CN112327301B (en) | Parameterized translational compensation rapid method under low signal-to-noise ratio based on subaperture GRFT | |
| CN113504509A (en) | Clutter suppression method for uniform acceleration airborne radar based on beam domain compensation | |
| CN114384484B (en) | Segmentation processing-based rapid coherent accumulation method for uniform accelerated motion target | |
| CN105548987B (en) | A kind of continuous wave radar aimed acceleration blind estimating method | |
| CN116449320A (en) | Long-time accumulation and parameter estimation method under frequency agile radar system | |
| CN113267756B (en) | Space-based radar space moving target detection and parameter estimation method and system | |
| CN115508786A (en) | Coherent accumulation method based on Radon transformation and matched filtering compensation |
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 |