CN111198374B - Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression - Google Patents
Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression Download PDFInfo
- Publication number
- CN111198374B CN111198374B CN202010032001.XA CN202010032001A CN111198374B CN 111198374 B CN111198374 B CN 111198374B CN 202010032001 A CN202010032001 A CN 202010032001A CN 111198374 B CN111198374 B CN 111198374B
- Authority
- CN
- China
- Prior art keywords
- frequency
- signal
- doppler
- pulse
- interference
- 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.)
- Active
Links
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
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/02—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems using reflection of acoustic waves
- G01S15/50—Systems of measurement, based on relative movement of the target
- G01S15/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
- G01S15/582—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of interrupted pulse-modulated waves and based upon the Doppler effect resulting from movement of targets
-
- 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
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/02—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems using reflection of acoustic waves
- G01S15/50—Systems of measurement, based on relative movement of the target
-
- 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
- G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
- G01S7/523—Details of pulse systems
- G01S7/526—Receivers
- G01S7/527—Extracting wanted echo signals
- G01S7/5273—Extracting wanted echo signals using digital techniques
-
- 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
- G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
- G01S7/539—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Acoustics & Sound (AREA)
- Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
Abstract
A Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression belongs to the technical field of underwater moving target detection. The invention aims to solve the problems of high false alarm probability and low detection probability of underwater moving target detection. The invention adopts the broadband Doppler sensitive signal to simultaneously ensure the speed resolution and the distance resolution, and achieves the purposes of reverberation resistance and interference resistance according to the difference of the characteristics of reverberation/interference and Doppler frequency shift of a moving target; and interference suppression is carried out in a Doppler frequency shift domain through the Doppler frequency shift characteristics of single pulse signals and multi-pulse signals, target interference separation is carried out in a time domain by adopting a matched filtering technology, and interference spatial filtering is carried out in a spatial domain by adopting a beam forming technology. The underwater acoustic detector is mainly used for underwater acoustic detection of moving targets.
Description
Technical Field
The invention belongs to the technical field of underwater moving target detection, and relates to an underwater acoustic detection method for a moving target with a Doppler sensitive signal.
Background
In the field of underwater acoustic detection, both an active detection mode and a passive detection mode are main means for target detection. Due to the development of the underwater target stealth technology, the performance of a passive detection mode based on target radiation noise is obviously reduced, while the performance of an active detection mode based on target echo is reduced, but the stealth capability in a non-backscattering direction is limited, so that the active detection, particularly the multi-base detection, has a great prospect in the field of underwater target detection.
Meanwhile, the active detection mode still has problems and technical problems:
(1) The detection environment is complex and the false alarm probability is high. Interface influence: random nonuniformity of an ocean interface can cause acoustic scattering and propagation fluctuation, underwater acoustic channel multipath is formed through multiple interface reflections, and a false target generated by a complex multipath structure causes high false alarm probability; reverberation effect: reverberation is the main interference of active sonar, is generated along with sonar emission signals, is the superposition of scattering signals generated by a large number of irregular scatterers in the ocean, and severely limits the sonar operating distance and the detection performance.
(2) The signal-to-noise ratio is low, and the detection probability is low. Here, noise is broad and includes noise, reverberation, and clutter background. The reason for the low signal-to-noise ratio is mainly: noise, reverberation and clutter levels in the background environment are high; the target intensity is low, the scattering intensity is easily influenced by water motion and self posture, and the echo is weak and fluctuant.
Disclosure of Invention
The invention aims to solve the problems of high false alarm probability and low detection probability of underwater moving target detection.
A Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression comprises the following steps:
acquiring digital signals which are received by N array elements and subjected to AD conversion, wherein the time domain sampling point number of each pulse echo signal is M, the acquisition coprocessing pulse echo number is P, and storing the acquired data into a P multiplied by N multiplied by M three-dimensional data matrix D (P, i, M), wherein P is a pulse echo serial number, and P =1, 2.., P; i is the array element number, i =1, 2.., N; m is a time domain sampling point sequence number, M =1, 2.., M;
taking out signals of each pulse echo, respectively passing the signals through a band-pass filter, namely, respectively passing D (1, i, M), D (2, i, M),. Ang., D (P, i, M) through the band-pass filter to obtain S (1, i, M), S (2, i, M),. Ang., S (P, i, M), and combining to obtain a P × N × M three-dimensional data matrix S (P, i, M);
interference suppression is carried out in a Doppler frequency shift domain based on multi-pulse signals, and the same time delay unit pulse data sequence S due to strong static interference Tau interference The frequency spectrum of (p) is a sinc function at 0Hz, so that the strong static interference can be inhibited to the maximum extent and the target echo information can be reserved by filtering the 0Hz main lobe;
step 3, single pulse frequency-distance-direction three-dimensional signal processing:
estimating Doppler frequency shift value range of Doppler filter bank according to maximum speed of target movementDetermining Doppler frequency value precision according to signal frequency resolution, and recording the Doppler frequency shift value of each matched filter in the filter bank as fd = fd 1 ,fd 2 ,...,fd r ；
Selecting a fixed array element i 0 And the number of transmission pulses p is fixed 0 The matched filter input signal is a one-dimensional vector R (p) taken from a three-dimensional matrix 0 ,i 0 M), setting the transmission reference signal as h (m), and then the single-pulse frequency-distance two-dimensional processing method is as follows:
F(p 0 ,i 0 ,k,fd)＝E{R(p 0 ,i 0 ,m+k)·h * (m)·e j2π·fd·m }
F(p 0 ,i 0 k, fd) is a single pulse frequency-distance two-dimensional processing result, wherein k is a time delay sampling point serial number, and k =1, 2.. Multidot.m; fd is the Doppler shift index, fd = fd 1 ,fd 2 ,...,fd r (ii) a E {. Cndot } represents averaging; h is * (m) is a conjugated form of h (m);
sequentially taking each pulse echo of each array element channel as the input of a Doppler filter bank, and finally obtaining a four-dimensional data matrix F (P, i, k, fd) of P multiplied by N multiplied by M multiplied by r;
taking an N-element equally spaced linear array as an example, setting the array element interval as d, and setting c as sound velocity and the included angle between the echo direction and the array normal direction, that is, the target azimuth as θ when the target satisfies the far-field condition, the delay difference between adjacent elements is:
by the p-th 0 Sub-pulse echo for example, matched filter reference signal frequency shift fd 0 For example, each array element signal is F (p) 0 ,i,k,fd 0 )；
Performing fs point DFT operation on the signals of the array elements i, wherein N array elements are required to be subjected to DFT operation for N times;
the signal bandwidth is evenly divided into Y frequency bands, and the central frequency of each frequency band is f y Representing; using array element 1 as reference, time domain interpolation of adjacent array element signalsInto different time delays Δ τ i I.e. multiplying different time factors in the frequency domain
Sum all frequency bands and sum
Substituting into it, namely:
mixing X Y (p 0 ,i,f,θ,fd 0 ) And the result is subjected to IDFT conversion and returned to the time domain, and the time domain results of all array elements are summed and output:
and (3) obtaining a distance-direction two-dimensional processing result of the single pulse echo under a certain frequency by combining an active sonar transceiving combined system model:
B(p 0 ,ρ,θ,fd 0 ) The distance-direction two-dimensional processing result is the distance-direction two-dimensional processing result of the single pulse echo under a certain frequency;
the first pulse echo data of each array element is taken out, and the result of each frequency shift matching is used as the input of the beam forming process, namely, the first pulse echo data of each array element is respectively applied to F (1, i, k, fd) 1 ),F(1,i,k,fd 2 ),...,F(1,i,k,fd r ) B (1, rho, theta, fd) is obtained after the beam forming treatment 1 ),B(1,ρ,θ,fd 2 ),...,B(1,ρ,θ,fd r ) The data are frequency-distance-azimuth three-dimensional signal processing results of the first pulse echo data, wherein rho represents a distance, and theta represents an azimuth angle; then, the second pulse echo data of each array element is taken out for the same processing to obtain B (2, rho, theta, fd) 1 ),B(2,ρ,θ,fd 2 ),...,B(2,ρ,θ,fd r ) Cycle ofLoop processing until the last pulse echo data to obtain B (P, rho, theta, fd) 1 ),B(P,ρ,θ,fd 2 ),...,B(P,ρ,θ,fd r ) (ii) a And finally, storing the four-dimensional data matrix B (p, rho, theta, fd) to obtain frequency-distance-azimuth information of different pulse echoes, thereby realizing the underwater acoustic detection of the moving target.
Further, the process of obtaining a new three-dimensional data matrix S (P, i, M) of P × N × M by the bandpass filter of each pulse-back signal of each array element channel in step 1 is as follows:
and (3) taking out signals of each pulse echo, and respectively passing the signals through a band-pass filter, namely, respectively passing D (1, i, M), D (2, i, M),. And D (P, i, M) through the band-pass filter to obtain S (1, i, M), S (2, i, M),. And S (P, i, M), and combining to obtain a P multiplied by N multiplied by M three-dimensional data matrix S (P, i, M).
Further, the process of filtering out the 0Hz frequency component of the multi-pulse data sequence with the same time delay unit by using the interference doppler shift filter based on the Least Mean Square (LMS) adaptive algorithm to obtain the three-dimensional data matrix R (p, i, m) after interference suppression includes the following steps:
the interference suppression based on the Doppler shift characteristic of the multi-pulse signal is completed based on a Least Mean Square (LMS) adaptive filter, and the input signal is assumed as the ith 0 Number array element at time delay point m 0 P times of echo data of (a) to (b), i.e.:
x(n)＝S(p,i 0 ,m 0 ),p＝1,2,...,P，n＝1,2,...P
the adaptive filtering y-channel output is:
y(n)＝w s (n)·x s (n)+w c (n)·x c (n)
wherein x is s (n)＝sinω o n,x c (n)＝cosω o n is two mutually orthogonal reference signals, ω 0 For interfering Doppler shifts, the strong static interfering Doppler shift is 0Hz, so x s (n) is constantly 0, x c (n) is constant 1, and the length is equal to the length of the input signal; the 0Hz component in the suppressed input is learned step by step through the residual, i.e.:
w s (n+1)＝w s (n)+2λ·ε(n)·x s (n)
w c (n+1)＝w c (n)+2λ·ε(n)·x c (n)
wherein λ =2 π Bw/fs is the learning step length; epsilon (n) = x (n) -y (n) is a residual error; bw is the filter-3 dB bandwidth parameter, to ensure that the sequence S of successive pulse samples is taken τ (j) Filtering out 0Hz components in the frequency domain, wherein Bw is not less than the width of the 0Hz main lobe in the frequency domain after the expansion caused by the environmental influence;
when the filtering effect reaches balance along with the self-adaptation of the filter to be filtered, taking the output epsilon (n) of the residual channel as the output R (p, i) of the filter 0 ,m 0 ) Namely:
R(p,i 0 ,m 0 )＝ε(n),n＝1,2,...P,p＝1,2,...P
and (3) performing the processing on the P times of echo data of each array element and each time delay point to obtain a three-dimensional data matrix R (P, i, m) subjected to interference suppression.
Further, the fs point DFT operation on the array element i signal is as follows:
further, the process of obtaining the distance-direction two-dimensional processing result of the single-pulse echo under a certain frequency by combining the active sonar transmitting-receiving combined system model comprises the following steps:
mixing X Y (p 0 ,i,f,θ,fd 0 ) And the result is subjected to IDFT conversion and returned to a time domain, and the time domain results of all array elements are summed and output:
the relation between the time delay sampling point sequence number k and the distance rho of the active sonar transceiving system model is as follows:
will be formula B' (p) 0 ,i,k,θ,fd 0 ) The result is summed over all array elements and output
Substituting to obtain:
in order to solve the problems of high false alarm probability and low detection probability existing in complex detection environment, the invention respectively provides corresponding technical schemes:
1) In the aspect of signal system: active sonar generally adopts a signal form system combining long single-frequency pulse and hyperbolic frequency modulation pulse, and respectively ensures speed resolution and distance resolution. The invention adopts the broadband Doppler sensitive signal to simultaneously ensure the speed resolution and the distance resolution, and achieves the purposes of reverberation resistance and interference resistance according to the difference of the characteristics of reverberation/interference and Doppler frequency shift of a moving target.
2) The space-time-frequency joint signal processing method comprises the following steps: the target signal-to-noise ratio, the signal-to-noise ratio and the signal-to-interference ratio of the active sonar are low, for example, the interference-to-signal ratio of direct wave interference of the bistatic active sonar can reach more than 50 dB. The invention carries out interference suppression in a Doppler frequency shift domain through the Doppler characteristic of a single pulse signal and the Doppler frequency shift characteristic of a multi-pulse signal, adopts a matched filtering technology to carry out target interference separation in a time domain, and adopts a beam forming technology to carry out interference spatial filtering in a spatial domain.
Therefore, the invention has the following beneficial effects:
(1) Because the interference of static targets, reverberation and the like is concentrated in a zero Doppler region, and the moving target has certain Doppler, the method adopts the broadband Doppler sensitive signal for detection, can separate the moving target and the interference in a time domain and a Doppler frequency shift domain, improves the detection probability, and reduces the false alarm probability.
(2) In step 2, the broadband system cannot set a trap of an interference frequency point to perform waveform-level filtering like the narrowband system, and the doppler frequency shift of strong coherent interference can be estimated by state transition between multi-pulse echoes of the interference. Therefore, the invention aims at broadband signals and carries out interference suppression based on the Doppler frequency shift characteristic of the multi-pulse signals.
(3) In step 3, the monopulse frequency-distance-direction three-dimensional signal processing method separates the interference and the target from the three-dimensional parameter space on one hand, and obtains the high-dimensional parameter estimation of the target on the other hand. By using the matched filtering technology, not only can the interference suppression be carried out on the time domain, but also the time-width bandwidth processing gain can be obtained. The matched filter group technology of different frequency shifts can be used for not only carrying out interference suppression in a frequency domain, but also obtaining a target Doppler shift estimated value. By using the beam forming technology, not only can the interference suppression be carried out in the space domain, but also the space processing gain can be obtained. Therefore, the monopulse frequency-distance-direction three-dimensional signal processing method can effectively improve the signal-to-noise ratio and reduce the false alarm probability.
Drawings
FIG. 1 is a general block diagram of the present invention for signal processing of underwater moving object detection;
fig. 2a is a partial enlarged view of step one in fig. 1, fig. 2b is a partial enlarged view of step two in fig. 1, and fig. 2c is a partial enlarged view of step three in fig. 1.
FIG. 3a is a schematic diagram of the frequency-range-azimuth three-dimensional processing result of a single pulse echo in the present invention; FIG. 3b is a diagram showing the three-dimensional processing result of the pulse echo number-range-azimuth in frequency matching according to the present invention;
fig. 4a to 4d are distance-azimuth two-dimensional processing result diagrams during frequency matching before and after single-pulse interference suppression in a simulation experiment of the present invention, where fig. 4a and 4b are distance-azimuth two-dimensional processing result diagrams during frequency matching before single-pulse interference suppression corresponding to fd =0 and fd = -3.3, respectively, and fig. 4c and 4d are distance-azimuth two-dimensional processing result diagrams during frequency matching after single-pulse interference suppression corresponding to fd =0 and fd = -3.3, respectively;
fig. 5a to 5c are graphs of two-dimensional distance-frequency processing results at a fixed angle before and after single-pulse interference suppression in a simulation experiment of the present invention, where fig. 5a and 5b are graphs of two-dimensional distance-frequency processing results at a fixed angle before single-pulse interference suppression corresponding to an interference azimuth and a target azimuth, respectively, and fig. 5c and 5d are graphs of two-dimensional distance-frequency processing results at a fixed angle after single-pulse interference suppression corresponding to an interference azimuth and a target azimuth, respectively.
Detailed Description
The first embodiment is as follows: the present embodiment is described with reference to fig. 1 and fig. 2a to 2c, and fig. 1 is a general block diagram of underwater moving object detection signal processing; in order to clearly show fig. 1, the method is performed with respect to fig. 1, and fig. 2 is a partial enlarged view of fig. 1, wherein fig. 2a is a partial enlarged view of step one of fig. 1, fig. 2b is a partial enlarged view of step two of fig. 1, and fig. 2c is a partial enlarged view of step three of fig. 1.
The embodiment is a Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression, which comprises the following steps:
when an active sonar system is adopted for detection, the receiving hydrophone array is provided with N array element channels, the pulse period is T, and the sampling rate is fs. The number of coprocessing pulse echoes is P, and the data volume per pulse echo is M = T · fs. Storing the data in a P N M three-dimensional data matrix D (P, i, M), wherein P is a pulse echo number, and P =1, 2.., P; i is the array element number, i =1, 2.., N; m is the time domain sample point number, M =1, 2.
Each pulse back signal of each array element channel passes through a band-pass filter to obtain a new P multiplied by N multiplied by M three-dimensional data matrix S (P, i, M).
the design of the interference filter based on the doppler characteristic needs to be comprehensively considered in combination with the speed of the target, the speed of the interference, and the stability of the underwater acoustic environment. The interference suppression of the narrow-band system can set the direct waveform level filtering of the wave trap of the interference frequency point on the frequency domain according to the characteristics that the interference and the moving target speed are different and the frequency is different. In order to actually meet the distance resolution required by target detection at the same time, a broadband system is often selected, and due to the limitation of underwater sound velocity and underwater target velocity, most of the frequency band ranges of interference and targets are overlapped or have little difference even if the velocities are different, so that a wave trap for interfering a frequency point cannot be arranged to perform waveform-level filtering like a narrow-band system, and therefore the invention provides a wave trap for interfering Doppler frequency shift in a Doppler shift domain instead of a wave trap for interfering the frequency point in a frequency domain.
The doppler shift of a strong coherent interferer can be estimated by interfering inter-multi-echo state transitions. When the receiving and transmitting are relatively static, fixing a distance point (time delay point), continuously observing the P pulse echoes to obtain a same time delay unit pulse data sequence with P sampling points in total, and recording as S τ (P), P =1, 2. For static strong interference, its spectrum is a sinc function at 0 Hz. Ideally, the main lobe width of the sinc function depends on the signal time length, the single-sided main lobe width is 1/NT, N is the number of pulse loops, and T is the pulse period. In practical situations, due to the influence of signal fluctuation and multipath, the frequency shift of the static strong interference will generate a certain spread, resulting in broadening of the main lobe of the sinc function. For moving target echoes with low signal-to-noise ratio, the moving target arrival time delays of different pulse echoes are different due to the motion state of the target, and the target distance difference corresponding to different pulse echoes exceeds a signal distance resolution unit Tau target (p) S when S is not significantly periodic and S is significantly disturbed by noise with a low signal-to-noise ratio Tau target And (p) the energy distribution in the frequency domain is uniform, and the bandwidth is-1/2T to 1/2T. When the echo of the moving target is submerged by strong interference, the same time delay unit pulse data sequence S τ (p) then is S Tau interference (p) and S Tau target And (p) superposition, wherein the frequency spectrum of the superposition is in a sinc function form at 0Hz with raised sidelobe fluctuation, most of interference energy is concentrated in a main lobe at 0Hz, and most of moving target echo signal and noise energy is distributed in a plurality of sidelobes outside the frequency of 0 Hz. Therefore, when interference suppression is performed in the domain, the main lobe of the frequency component of 0Hz should be completely filtered, so that static strong interference can be suppressed to a great extent, and target echo information is retained.
Based on the analysis, an interference Doppler frequency shift filter based on Least Mean Square (LMS) self-adaptive algorithm can be designed to filter multi-pulse same time delayThe 0Hz frequency component of the unit data sequence, the other frequency components being retained. Inputting P times of echo data of the ith array element at a time delay point m, and using the array element i 0 Sum delay point m 0 For example, the input signal is S (p, i) 0 ,m 0 ) P =1,2, P, adaptive notch to output e a residual channel as a doppler filtered output signal R (P, i) 0 ,m 0 ),p＝1,2,...,P。
And traversing all the time delay points m and the array elements i to obtain three-dimensional matrix data R (p, i, m) of which all the output signals are subjected to interference suppression for the time domain.
The interference suppression based on the Doppler shift characteristic of the multi-pulse signal is completed based on a Least Mean Square (LMS) adaptive filter, and an input signal is assumed to be the ith signal 0 Number array element at time delay point m 0 The P-th echo data of (a) constitutes a signal, namely:
x(n)＝S(p,i 0 ,m 0 ),p＝1,2,...,P，n＝1,2,...P
the adaptive filtering y-channel output is:
y(n)＝w s (n)·x s (n)+w c (n)·x c (n)
wherein x s (n)＝sinω o n,x c (n)＝cosω o n is two mutually orthogonal reference signals, ω 0 For interfering Doppler shifts, the strong static interfering Doppler shift is 0Hz, so x s (n) is constantly 0, x c And (n) is constant 1, and the length of the input signal is equal to that of the input signal. The 0Hz component in the input is suppressed by residual progressive learning, i.e.:
w s (n+1)＝w s (n)+2λ·ε(n)·x s (n)
w c (n+1)＝w c (n)+2λ·ε(n)·x c (n)
wherein λ =2 π Bw/fs is the learning step size. ε (n) = x (n) -y (n) is a residual error. Bw is the filter-3 dB bandwidth parameter, to ensure that the sequence S of successive pulse samples is taken τ (j) The 0Hz component in the frequency domain is filtered out, bw should be no less than the width of the 0Hz main lobe in its frequency domain after the expansion by environmental influences.
The filtering effect is adaptive to the filter to be filteredWhen the balance is reached, taking the output epsilon (n) of the residual channel as the output R (p, i) of the filter 0 ,m 0 ) Namely:
R(p,i 0 ,m 0 )＝ε(n),n＝1,2,...P,p＝1,2,...P
and (3) performing the processing on the P times of echo data of each array element and each time delay point to obtain a three-dimensional data matrix R (P, i, m) subjected to interference suppression.
Step 3, single pulse frequency-distance-direction three-dimensional signal processing:
after passing through a matched filter, a common pulse compression signal is compressed into narrow pulses, so that the resolution of the sonar can be improved, and the signal-to-noise ratio gain can be improved. The effect of the matched filter is related to the signal form and signal parameters selected by the active sonar transmitting end. For the broadband Doppler sensitive signal, a frequency-distance two-dimensional detection result can be obtained by a time domain signal received by an array element through a matched filter bank. The matched filter bank corresponds to a series of reference signals with different Doppler frequency shifts, the Doppler frequency shift value range is determined by the maximum motion speed of the target, the Doppler frequency shift value precision is determined by the frequency resolution of the signals and can be half of the frequency resolution, namely 1/2T, and the Doppler frequency shift value of each matched filter in the filter bank is recorded as fd = fd 1 ,fd 2 ,...,fd r 。
The input signal of the single-pulse frequency-distance-direction three-dimensional signal processing is a signal after interference suppression processing based on the Doppler frequency shift characteristic of the multi-pulse signal, namely, the output result of step 2. Due to the moving state of the target and the doppler sensitivity of the signals used, the signals of different pulse echo periods all have different doppler shifts. By the p-th 0 Sub echo ith 0 Signal R (p) of number array element 0 ,i 0 M) is taken as an example, and taken out from the three-dimensional matrix R (p, i, m) as an input of the matched filter, and the transmitted reference signal is taken as h (m), then the processing method is as follows:
F(p 0 ,i 0 ,k,fd)＝E{R(p 0 ,i 0 ,m+k)·h * (m)·e j2π·fd·m }
k＝1,2,...,M,fd＝fd 1 ,fd 2 ,...,fd r (1)
F(p 0 ,i 0 k, fd) is the single pulse frequency-distance two-dimensional processing result, wherein k is the time delay sampling point serial number, k =1, 2. fd is the number of Doppler shifts, fd = fd 1 ,fd 2 ,...,fd r (ii) a E {. Cndot } represents an average value, h * (m) is a conjugated form of h (m).
And sequentially taking each pulse echo of each array element channel as the input of a Doppler filter bank, and finally obtaining a four-dimensional data matrix F (P, i, k, fd) of P multiplied by N multiplied by M multiplied by r.
Beamforming is a processing technique for the array to be robust against noise in the spatial domain, and for wideband signals, a frequency-domain beamforming technique should be used. A matrix composed of N elements has a spatial gain of 10lgN if the condition that the noise received by each element is independent of each other is satisfied. Taking an N-element equal-interval linear array as an example, setting the array element interval as d, and setting c as sound velocity when a target meets a far-field condition, and setting an included angle between an echo direction and an array normal direction, namely a target azimuth as theta, wherein a time delay difference between adjacent elements is as follows:
by the p-th 0 Sub-pulse echo for example, matched filter reference signal frequency shift fd 0 For example, each array element signal is F (p) 0 ,i,k,fd 0 ) (after interference suppression and matched filtering). Firstly, fs-point DFT operation is carried out on an array element i signal, namely:
n array elements in total, so equation (3) is performed N times.
Uniformly selecting J frequency points in the signal frequency band, and recording as f j J =1, 2. Based on array element 1, different time delays delta tau are inserted into the time domains of adjacent array element signals i I.e. multiplying different time factors in the frequency domain
Summing over all bins and substituting equation (2) into it, i.e.:
and (3) carrying out IDFT (inverse discrete Fourier transform) on the result of the formula and converting the result of the formula back to a time domain, and summing the time domain results of all array elements to output:
the relation between the time delay sampling point sequence number k and the distance rho can be known by an active sonar transceiving system model as follows:
and (3) summing and outputting the result of the formula (5) to all array elements and substituting the result (6) to obtain:
B(p 0 ,ρ,θ,fd 0 ) Is the p-th 0 Sub-pulse echo matched Doppler shift fd 0 And (5) processing the result in two dimensions of the distance and the direction.
Taking out the first pulse echo data of each array element, and using the result of each frequency shift matching as the input of beam forming process, i.e. for F (1, i, k, fd) 1 ),F(1,i,k,fd 2 ),...,F(1,i,k,fd r ) B (1, rho, theta, fd) is obtained after the beam forming treatment 1 ),B(1,ρ,θ,fd 2 ),...,B(1,ρ,θ,fd r ) That is, the frequency-range-azimuth three-dimensional signal processing result of the first pulse echo data, θ represents the azimuth. Then, the second pulse echo data of each array element is taken out for the same processing to obtain B (2, rho, theta, fd) 1 ),B(2,ρ,θ,fd 2 ),...,B(2,ρ,θ,fd r ) And circularly processing until the last pulse echo data to obtain B (P, rho, theta, fd) 1 ),B(P,ρ,θ,fd 2 ),...,B(P,ρ,θ,fd r ). And finally, storing the four-dimensional data matrix B (p, rho, theta, fd) to obtain the frequency-distance-direction information of different pulse echoes.
Examples
Simulation conditions are as follows: the transmitting signal form of the transmitting and receiving combined system is a 10-order m-sequence phase modulation signal, the pulse width is 1s, the bandwidth is 2kHz, the central frequency is 2kHz, the sampling rate fs is 10 times of the central frequency of the signal, the sound velocity c =1500m/s is set, the receiving array is a 12-element equal-spacing linear array, and the array element spacing is half wavelength. The distance between the target to be measured and the receiving array is 20m at the initial moment, the target moves linearly at a constant speed and is far away from the system, the speed is 5 knots (2.5 m/s), and the included angle between the moving direction and the array is 60 degrees. And a strong interference target is far away from the system 480m, the direction of the strong interference target forms an angle of 90 degrees with the array, each element continuously receives 100 pulse echoes, and the pulse period T =4s. The signal-to-noise ratio of the target echo is set to be 0dB, and the signal-to-noise ratio of the interference echo is set to be 30dB, namely the interference-signal ratio is set to be 30dB.
Firstly, preprocessing in step 1 is carried out, band-pass filtering is carried out on received signals, the filter passband is the signal bandwidth, and a three-dimensional data matrix S (p, i, m) is obtained, wherein p represents the number of pulse echoes for 100 times, i represents the number of array elements for 12 times, and m is the number of time domain sampling points for T x fs.
Then, step 2 is carried out, and array elements i are processed 0 The pulse echo signals are observed at different fixed sampling moments to obtain a continuous pulse echo sampling sequence S of strong interference, target echo and strong interference superposed target echo Tau interference (p)、S Tau target (p) and S Tau interference (p) superposition of S Tau target (p) of the formula (I). The interference suppression based on the LMS adaptive filter is designed, and the notch of the Doppler domain 0Hz component is carried out so as to achieve the purpose of suppressing the strong coherent interference. For the data of each array element i, a multi-pulse echo sequence of each sampling point m is taken as the input of an interference filter (hereinafter referred to as an interference filter) based on the Doppler frequency shift characteristic of a multi-pulse signal. The residual output epsilon (n) is taken as the interference filter output. Finally, the interference-filtered data matrix R (p, i, m), andthe data matrix S (p, i, m) before interference suppression is in the same dimension.
And finally, step 3, determining the Doppler frequency range of the matched filter group, and enabling the data R (p, i, m) subjected to interference suppression to pass through the matched filter group to obtain F (p, i, k, fd). Fig. 3a is a schematic diagram of a frequency-distance-direction three-dimensional processing result of any monopulse echo signal obtained by performing beamforming and storing all data to obtain B (p, ρ, θ, fd), where x and y axes represent distance and direction, respectively, and z axis represents pulses of different doppler frequencies. The echo number-distance-orientation three-dimensional processing result is schematically shown in fig. 3b, wherein the x-axis and the y-axis represent the distance and the orientation, respectively, and the z-axis represents different pulse echo numbers.
The simulation condition of 30dB of interference-to-signal ratio causes the echo signal to be completely covered by the side lobe of the matched filter with strong static interference, so that the Doppler frequency shift fd of the target echo can not be given by directly carrying out the matched filter 0 And distance information, which can be obtained from the interference suppressed matched filter result F (p, i, k, fd). To illustrate the interference suppression effect of step 2, all array element data of the 50 th pulse echo are taken, step 3 is directly carried out without interference Doppler filtering in step 2, and the frequencies of 0Hz and fd are obtained 0 The two-dimensional distance-orientation processing results are respectively shown in fig. 4a and 4b, and the doppler frequencies obtained in step 3 after the interference suppression are 0Hz and fd 0 Is processed in two dimensions, i.e. B (p) 50 ρ, θ, fd = 0) and B (p) 50 ,ρ,θ,fd 0 ) The energies in fig. 4a, 4b, 4c and 4d are all expressed in decibels and normalized by the same value, as shown in fig. 4c and 4d, respectively. In fig. 4a high level of static interference at 90 deg. and 480m is detected, and in fig. 4b only a strong interference is detected at the doppler frequency fd due to the high interference-to-signal ratio 0 The energy leakage of the target echo cannot be detected, and after step 2, in fig. 4c, the interference at 90 ° and 480m positions under 0Hz is greatly suppressed, the range sidelobe at 60 ° azimuth is the leakage of the target echo at 0Hz, and in fig. 4d, the doppler frequency is fd 0 The range and azimuth of the target can be successfully detected to be 60 degrees and 510m, and the range and azimuth result conforms to the simulation condition. Do not interfere with each other in step 2The doppler filtering is directly performed in step 3 to obtain two-dimensional distance-frequency processing results with angles of 90 ° and 60 ° as shown in fig. 5a and 5B, respectively, and the two-dimensional distance-frequency processing results with angles of 90 ° and 60 ° obtained in step 3 after the interference suppression, namely B (p) is performed 0 ρ, θ =90 °, fd) and B (p) 0 ρ, θ =60 °, fd) are shown in fig. 5c and 5d, respectively, the energy in fig. 5a, 5b, 5c and 5d is expressed in decibels and normalized by the same value. In fig. 5a, high energy interference at 0hz and 480m can be detected in the interference azimuth, and strong interference at 0hz and 480m in fig. 5b is azimuth side lobe at the target azimuth, so that any target information cannot be detected even in the target azimuth due to excessively high interference-to-signal ratio, and after step 2, strong interference at 0hz and 480m in the interference azimuth is greatly suppressed in fig. 5c, and the target distance and frequency shift of 510m, -3.3Hz can be detected in fig. 5d, which is consistent with the simulation condition. Therefore, the distance-direction-frequency information of different pulse echo moments can be obtained.
It should be noted that the detailed description is only for explaining and explaining the technical solution of the present invention, and the scope of protection of the claims is not limited thereby. It is intended that all such modifications and variations be included within the scope of the invention as defined in the following claims and the description.
Claims (4)
1. The Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression is characterized by comprising the following steps of:
step 1, data preprocessing:
acquiring digital signals which are received by N array elements and subjected to AD conversion, wherein the time domain sampling point number of each pulse echo signal is M, the acquisition coprocessing pulse echo number is P, and storing the acquired data into a P multiplied by N multiplied by M three-dimensional data matrix D (P, i, M), wherein P is a pulse echo serial number, and P =1, 2.., P; i is the array element number, i =1, 2.., N; m is a time domain sampling point number, M =1, 2.., M;
each pulse back signal of each array element channel passes through a band-pass filter to obtain a new P multiplied by N multiplied by M three-dimensional data matrix S (P, i, M);
step 2, an interference filter based on the Doppler frequency shift characteristic of the multi-pulse signal:
filtering out 0Hz frequency component of a multi-pulse same time delay unit data sequence by using an interference Doppler frequency shift filter based on a least mean square adaptive algorithm to obtain a three-dimensional data matrix R (p, i, m) subjected to interference suppression;
step 3, single pulse frequency-distance-direction three-dimensional signal processing:
estimating the Doppler frequency shift value range of a Doppler filter bank according to the maximum speed of target motion, determining the Doppler frequency value precision according to the signal frequency resolution, and recording the Doppler frequency shift value of each matched filter in the filter bank as fd = fd 1 ,fd 2 ,...,fd r ；
Selecting a fixed array element i 0 And the number of transmission pulses p is fixed 0 The matched filter input signal is a one-dimensional vector R (p) taken from a three-dimensional matrix 0 ,i 0 M), setting the transmission reference signal as h (m), and then the single-pulse frequency-distance two-dimensional processing method is as follows:
F(p 0 ,i 0 ,k,fd)＝E{R(p 0 ,i 0 ,m+k)·h * (m)·e j2π·fd·m }
F(p 0 ,i 0 k, fd) is a single pulse frequency-distance two-dimensional processing result, wherein k is a time delay sampling point serial number, and k =1,2,. Eta.m; fd is the Doppler shift index, fd = fd 1 ,fd 2 ,...,fd r (ii) a E {. Is mean of averaging; h is * (m) is a conjugated form of h (m);
sequentially taking each pulse echo of each array element channel as the input of a Doppler filter bank, and finally obtaining a four-dimensional data matrix F (P, i, k, fd) of P multiplied by N multiplied by M multiplied by r;
for an N-element equal-interval linear array, an array element interval is set as d, when a target meets a far field condition, c is set as a sound velocity, an included angle between an echo direction and an array normal direction, namely a target azimuth is set as theta, and a time delay difference between adjacent elements is as follows:
for p (th) 0 Sub-pulse echo, matched filter reference signal frequency shift fd 0 Each array element signal is F (p) 0 ,i,k,fd 0 )；
Performing fs-point DFT operation on the array element i signal, wherein N array elements are required to be subjected to DFT operation for N times; the fs point DFT operation on the array element i signal is as follows:
the signal bandwidth is evenly divided into Y frequency bands, and the central frequency of each frequency band is f y Represents; based on array element 1, different time delays delta tau are inserted into adjacent array element signal time domains i I.e. multiplying different time factors in the frequency domain
ω＝2πf y Sum all frequency bands and sum
Substituting into it, namely:
mixing X Y (p 0 ,i,f,θ,fd 0 ) And the result is subjected to IDFT conversion and returned to the time domain, and the time domain results of all array elements are summed and output:
combining an active sonar transmitting-receiving combined system model to obtain a distance-direction two-dimensional processing result of the monopulse echo under a certain frequency:
B(p 0 ,ρ,θ,fd 0 ) The distance-direction two-dimensional processing result is the distance-direction two-dimensional processing result of the single pulse echo under a certain frequency;
taking out the first pulse echo data of each array element, and using the result of each frequency shift matching as the input of beam forming process, i.e. for F (1, i, k, fd) 1 ),F(1,i,k,fd 2 ),...,F(1,i,k,fd r ) B (1, rho, theta, fd) is obtained after the beam forming treatment 1 ),B(1,ρ,θ,fd 2 ),...,B(1,ρ,θ,fd r ) The data are frequency-distance-azimuth three-dimensional signal processing results of the first pulse echo data, wherein rho represents a distance, and theta represents an azimuth angle; then, the second pulse echo data of each array element is taken out for the same processing to obtain B (2, rho, theta, fd) 1 ),B(2,ρ,θ,fd 2 ),...,B(2,ρ,θ,fd r ) And circulating the processing till the last pulse echo data to obtain B (P, rho, theta, fd) 1 ),B(P,ρ,θ,fd 2 ),...,B(P,ρ,θ,fd r ) (ii) a And finally, storing the four-dimensional data matrix B (p, rho, theta, fd) to obtain frequency-distance-azimuth information of different pulse echoes, thereby realizing the underwater acoustic detection of the moving target.
2. The method for detecting moving target underwater sound of doppler sensitive signal based on space-time-frequency joint interference suppression as claimed in claim 1, wherein the procedure of obtaining a new three-dimensional data matrix S (P, i, M) of P × N × M by the bandpass filter of each pulse back signal of each array element channel in step 1 is as follows:
and (3) taking out signals of each pulse echo, and respectively passing the signals through a band-pass filter, namely, respectively passing D (1, i, M), D (2, i, M),. And D (P, i, M) through the band-pass filter to obtain S (1, i, M), S (2, i, M),. And S (P, i, M), and combining to obtain a P multiplied by N multiplied by M three-dimensional data matrix S (P, i, M).
3. The method for detecting the moving target underwater sound of the doppler sensitive signal based on the space-time-frequency joint interference suppression as claimed in claim 1, wherein the step of filtering the 0Hz frequency component of the data sequence of the multi-pulse same delay unit by using the interference doppler shift filter based on the least mean square adaptive algorithm to obtain the three-dimensional data matrix R (p, i, m) after the interference suppression comprises the following steps:
the interference suppression based on the Doppler frequency shift characteristic of the multi-pulse signal is completed based on a least mean square adaptive filter, and an input signal is assumed to be an ith signal 0 Number array element at time delay point m 0 The P-th echo data of (a) constitutes a signal, namely:
x(n)＝S(p,i 0 ,m 0 ),p＝1,2,...,P，n＝1,2,...P (1)
the adaptive filtering y-channel output is:
y(n)＝w s (n)·x s (n)+w c (n)·x c (n) (2)
wherein x s (n)＝sinω o n,x c (n)＝cosω o n is two mutually orthogonal reference signals, ω o For interfering Doppler shifts, the strong static interfering Doppler shift is 0Hz, so x s (n) is constantly 0, x c (n) is constant 1, and the length is equal to the length of the input signal; the 0Hz component in the suppressed input is learned step by step through the residual, i.e.:
wherein λ =2 π Bw/fs is the learning step length; epsilon (n) = x (n) -y (n) is a residual error; bw is the filter-3 dB bandwidth parameter, to ensure that the sequence S of successive pulse samples is taken τ (j) Filtering out 0Hz components in the frequency domain, wherein the Bw is not less than the width of the 0Hz main lobe in the frequency domain after the expansion caused by the environmental influence;
when the filtering effect reaches balance along with the self-adaptation of the filter to be filtered, taking the output epsilon (n) of the residual channel as the output R (p, i) of the filter 0 ,m 0 ) Namely:
R(p,i 0 ,m 0 )＝ε(n),n＝1,2,...P,p＝1,2,...P (4)
and (3) performing the above processing on the P times echo data of each array element and each time delay point to obtain a three-dimensional data matrix R (P, i, m) subjected to interference suppression.
4. The method for underwater acoustic detection of moving targets of doppler sensitive signals based on space-time-frequency joint interference suppression according to claim 1, wherein the process of obtaining the distance-direction two-dimensional processing result of the monopulse echo at a certain frequency by combining with the active sonar transceiving combined system model comprises the following steps:
mixing X Y (p 0 ,i,f,θ,fd 0 ) And the result is subjected to IDFT conversion and returned to the time domain, and the time domain results of all array elements are summed and output:
the relation between the time delay sampling point sequence number k and the distance rho of the active sonar transceiving system model is as follows:
and (3) summing and outputting the result of the formula (5) to all array elements and substituting the result (6) to obtain:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010032001.XA CN111198374B (en) | 2020-01-13 | 2020-01-13 | Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010032001.XA CN111198374B (en) | 2020-01-13 | 2020-01-13 | Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111198374A CN111198374A (en) | 2020-05-26 |
| CN111198374B true CN111198374B (en) | 2022-10-25 |
Family
ID=70744863
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010032001.XA Active CN111198374B (en) | 2020-01-13 | 2020-01-13 | Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111198374B (en) |
Families Citing this family (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111948629B (en) * | 2020-07-31 | 2023-03-31 | 哈尔滨工程大学 | High-robustness large-Doppler single-frequency pulse signal detection method |
| WO2022027235A1 (en) * | 2020-08-04 | 2022-02-10 | Qualcomm Incorporated | Beam feedback based on object movement in wireless sensing |
| CN112114300B (en) * | 2020-09-14 | 2022-06-21 | 哈尔滨工程大学 | Underwater weak target detection method based on image sparse representation |
| CN112462321B (en) * | 2020-11-12 | 2024-02-13 | 南京世海声学科技有限公司 | Acoustic beacon signal interception processing method based on pulse matching accumulation |
| CN112630739B (en) * | 2020-11-30 | 2024-02-20 | 海鹰企业集团有限责任公司 | Broadband condition arbitrary speed copy generation method for comb spectrum signal |
| CN112801065B (en) * | 2021-04-12 | 2021-06-25 | 中国空气动力研究与发展中心计算空气动力研究所 | Space-time multi-feature information-based passive sonar target detection method and device |
| CN113671471B (en) * | 2021-08-18 | 2024-04-30 | 中国科学院声学研究所北海研究站 | Underwater sound target detection blind source separation method |
| CN113866771B (en) * | 2021-11-23 | 2024-06-18 | 中国航空工业集团公司洛阳电光设备研究所 | Underwater target detection method |
| CN114152774B (en) * | 2021-12-06 | 2022-07-26 | 中国科学院大学 | Flow velocity measuring method and device of liquid flow field, electronic equipment and storage medium |
| CN114460587B (en) * | 2022-04-11 | 2022-07-19 | 杭州应用声学研究所(中国船舶重工集团公司第七一五研究所) | Active sonar panoramic contact target rapid identification method |
| CN116299490B (en) * | 2023-01-17 | 2023-12-05 | 哈尔滨工程大学 | Underwater sound multi-target detection method based on self-adaptive Doppler filtering-Radon Fourier transformation |
| CN118033602B (en) * | 2024-04-08 | 2024-07-26 | 厦门大学 | FMCW-Lidar double-echo processing method, target detection device and storage medium |
| CN118311507B (en) * | 2024-04-18 | 2024-08-30 | 哈尔滨工业大学 | Method for suppressing coding cycle auxiliary radio frequency interference time domain, electronic equipment and storage medium |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6714482B2 (en) * | 2001-08-28 | 2004-03-30 | Rd Instruments, Inc. | Acoustic doppler channel flow measurement system |
| CN102680734B (en) * | 2006-09-28 | 2015-09-23 | 德立文亚迪仪器公司 | The system and method for acoustic doppler velocity process is carried out with phase array transducer |
| CN204495996U (en) * | 2011-10-26 | 2015-07-22 | 菲力尔系统公司 | broadband sonar receiver |
| CN103235294A (en) * | 2013-03-29 | 2013-08-07 | 电子科技大学 | Method for estimating weak signal separation on basis of positioning for external radiation sources |
| CN103344961B (en) * | 2013-07-05 | 2015-04-29 | 西北工业大学 | Passive acoustic Doppler phase position method of joint measurement of ship speed and distance |
| CN106597407B (en) * | 2016-12-06 | 2019-05-07 | 西安电子科技大学 | More stellar associations are the same as lower weak echo signal time delay and Doppler frequency shift combined estimation method |
| CN106872968A (en) * | 2017-03-14 | 2017-06-20 | 南昌大学 | A kind of external illuminators-based radar Weak target detecting method based on ofdm signal |
| CN108226879B (en) * | 2017-12-21 | 2021-08-13 | 北京遥感设备研究所 | SAR terrain scattering interference suppression method based on multiple channels |
-
2020
- 2020-01-13 CN CN202010032001.XA patent/CN111198374B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN111198374A (en) | 2020-05-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111198374B (en) | Doppler sensitive signal moving target underwater sound detection method based on space-time-frequency joint interference suppression | |
| CA2540596C (en) | Sonar system and process | |
| EP1938126B1 (en) | Sonar system and method providing low probability of impact on marine mammals | |
| Su et al. | Adaptive beamforming for nonstationary HF interference cancellation in skywave over-the-horizon radar | |
| CN108872970A (en) | Graing lobe method of discrimination suitable for general equidistant thinned array simple signal Wave beam forming | |
| CN109814070A (en) | Range ambiguity clutter suppression method based on false impulse | |
| CN105954729B (en) | The anti-distance of radar-velocity joint cheating interference adaptive iteration filtering method | |
| CN104101868B (en) | Radar multi-false-target jamming suppressing method based on interference space reconstruct | |
| EP2317335B1 (en) | Improved beamforming method for analysing signals received by a transducer arrray, and relative detection system | |
| Techau et al. | Performance bounds for hot and cold clutter mitigation | |
| CN116520279A (en) | Sea clutter suppression method | |
| CN115267721B (en) | Ground moving target radial velocity estimation method based on double-frequency SAR | |
| Lin et al. | New techniques for radar coherent range ambiguity resolution | |
| CN113238194B (en) | Broadband phased array radar anti-decoy interference method based on fractional domain-frequency domain processing | |
| WO2013132205A1 (en) | Target detection system and method | |
| Ślesicka et al. | The performance of a linear STAP processor for radar signal processing | |
| CN111665475A (en) | Radar main lobe interference suppression method and device, electronic equipment and storage medium | |
| Xenaki et al. | Sparse MIMO synthetic aperture sonar processing with distributed optimization | |
| Chen et al. | Iterative adaptive approach for wide-band active sonar array processing | |
| Mansour et al. | PC-based real-time active sonar simulator | |
| RU2812727C1 (en) | Method of radio-electronic protection of ground-based all-round radar and device for its implementation | |
| CN113126037B (en) | MTI-based clutter background sidelobe cancellation method | |
| Pillai et al. | Wideband STAP (WB-STAP) for passive sonar | |
| Ruggiano et al. | Experiments showing an improvement of angular resolution by lmmse-based processing | |
| Schröder et al. | Study on pulse form design for monostatic MIMO sonar systems |
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 |