CN112269164B - Weak target positioning method based on interference structure matching processing under deep sea reliable acoustic path - Google Patents
Weak target positioning method based on interference structure matching processing under deep sea reliable acoustic path Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- 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
- G01S15/06—Systems determining the position data of a target
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/88—Sonar systems specially adapted for specific applications
- G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- 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
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Abstract
The invention relates to a weak target positioning method based on interference structure matching processing under a deep sea reliable acoustic path, which aims at the practical problem that a multi-path interference characteristic is submerged by noise when the passive positioning receiving signal-to-noise ratio of a sound source is low, and the sound source depth cannot be accurately estimated by utilizing the method, and a multi-beam output power spectrum is spliced so as to extract the multi-path interference characteristic submerged by the noise. According to the phenomenon that the propagation delay difference of the sea surface sound source direct wave and the sea surface reflected wave is sensitive along with the depth change, the characteristic that a matched filter is sensitive to frequency mismatch is utilized, and the power spectrum of a received signal and the copy power spectrum are subjected to matched filtering processing, so that sound source position information is obtained under the condition of low signal-to-noise ratio. The weak target passive positioning method based on interference structure matching processing can estimate the target depth and horizontal distance under lower signal-to-noise ratio.
Description
Technical Field
The invention belongs to underwater acoustic array signal processing, and relates to a weak target positioning method based on interference structure matching processing under a deep sea reliable acoustic path.
Background
The deep sea reliable acoustic path (RAP: reliable acoustic path) is a channel of acoustic propagation that is specific to deep sea. The RAP occurs if the transducer is below the critical depth in the deep sea (the speed of sound at the critical depth is equal to the speed of sound near the sea surface) where an acoustic propagation path from the sea surface to the transducer is formed. The acoustic propagation path is not affected by off-shore effects or by subsea interactions, and the propagation signal is stable and reliable, hence the term reliable acoustic path (Rui D,Kun-De Y,Yuan-Liang M,et al.A reliable acoustic path:Physical properties and a source localization method[J].Chinese Physics B,2012,21(12):124301.).
At present, the existing method is to place a receiving hydrophone in the deep sea, and passively detect an offshore underwater target by extracting RAP multi-path interference structural features. In many cases, however, the target radiation noise level to be detected is low, so that the signal-to-noise ratio at the deep sea receiving hydrophone is low, which tends to result in the multipath interference characteristics being swamped by noise. At this time, the underwater target detection problem becomes a weak target detection problem, and an excessively low signal-to-noise ratio makes it difficult for the existing method to effectively extract the interference structure frequency, resulting in a decrease in detection performance.
Disclosure of Invention
Technical problem to be solved
In order to avoid the defects of the prior art, the invention provides a weak target positioning method based on interference structure matching processing under a deep sea reliable acoustic path.
Technical proposal
A weak target positioning method based on interference structure matching processing under a deep sea reliable acoustic path is characterized by comprising the following steps:
Step 1: setting a single multi-element vertical array below a critical depth to obtain a frequency domain broadband beam output of the vertical array, and obtaining a multi-element vertical array acquisition target radiation noise, wherein the length of a section of acquired time domain signal is 60 seconds to 600 seconds;
Dividing an acquired time domain signal into M sub-segments, and carrying out Fourier transform on each sub-segment to obtain M sub-segment spectrums;
Kmfl＝[x1,m fl,x2,m fl,x3,m fl,...,xN,m fl]T
Wherein, K m(fl) is the M (m=1, 2, M) the value at the mid-frequency point f l in the sub-band spectrum, x nm(fl) represents the value of the N (n=1, 2, N) values at frequency point f l in the M-th sub-band spectrum of array elements, N being the number of array elements, [ ] T represents transpose;
the time length of each sub-segment ranges from 4 seconds to 30 seconds, adjacent sub-segments are overlapped in time, and the overlap ratio range is defined as the time length of an overlapped part divided by the time length of a single sub-segment, and is 0% to 75%;
Performing broadband multi-beam processing on the frequency spectrums of all sub-bands by using a linear array frequency domain beam forming method, and performing beam scanning in the pitching direction so as to obtain frequency domain broadband beam outputs at a plurality of pitching angles;
pm(fl,θ)＝[w(fl,θ)]HKm(fl)
Wherein, p m(fl, θ) represents the beam output with the beam scanning pitch angle θ and the frequency f l in the m-th section of spectrum, w (f l,θ)＝[1,eikdcosθ,ei2kdcosθ,...,ei(N-1)kdcosθ]T is the weighting vector of conventional beam forming, [ ] H represents the conjugate transpose, d is the array element spacing, k=2pi f l/c0 is the wave number, and c 0 is the reference sound velocity used by the beam former;
The m-th sub-segment beam output spectrum with steering angle θ is:
pm(θ)＝[pm(f1,θ),pm(f2,θ),...,pm(fL,θ)]T,
Wherein L represents the number of frequency points;
Step 2, splicing the output of the vertical array frequency domain broadband beam:
Multiplying conjugate vectors of the output points of the multi-section frequency domain broadband wave beams on each pitching angle to obtain multi-section power spectrums:
Sm(θ)＝pm(θ)⊙pm *(θ)＝[pm *(f1,θ),pm *(f2,θ),...,pm *(fL,θ)]T,(4)
Wherein S m (θ) represents the output power spectrum with the m-th sub-segment beam scanning pitch angle θ, and then, by;
splicing a plurality of power spectrums of adjacent time periods, thereby obtaining a longer power spectrum, denoted by S (θ), which is a power spectrum of a received signal on the beam:
S(θ)＝[p1(θ)T,p2(θ)T,...,pM(θ)T]T；
Step 3, modeling of copy power spectrum of each grid point, and matched filtering processing of the received signal power spectrum and copy power spectrum on each wave beam:
Evenly dividing grids in the horizontal distance and depth direction in the detection range, calculating the time delay difference delta tau at the geometric center of the vertical receiving array when the target is positioned on each grid point, and obtaining the copy power spectrum of each grid point when the receiving signals are the same in the frequency band range:
wherein f is frequency, H (f, theta, z a) is a copy power spectrum calculated by sound field software under the assumption of target depth z a and pitch angle theta a, Representing using B to carry out matched filtering treatment on A and outputting a maximum value;
The output result on the grid point is t (z a,θa), so that a vertical angle-depth blur map is obtained;
step 4, calculating the corresponding relation between the pitch angle and the horizontal distance offline by utilizing sound field software, converting the pitch angle-depth fuzzy map into a horizontal distance-depth positioning fuzzy map, and searching a peak value to obtain a positioning result:
Taking any depth in the detection range, dividing the horizontal distance in the detection range, and calculating the pitch angle average value theta of the direct wave and the sea surface reflected wave at the geometric center of the vertical receiving array when the target is positioned at each horizontal distance grid through sound field software in an off-line mode, so that the corresponding relation between the pitch angle and the horizontal distance is obtained:
Wherein: θ d represents the pitch angle of the direct wave, and θ sr represents the pitch angle of the sea surface reflected wave;
Converting the pitching angle into horizontal depth to obtain a horizontal distance-depth positioning blur map, wherein the output result of each grid point is t (z a,ra);
Finally, obtaining a positioning result through searching the peak value:
(rreal,sreal)＝arg{max[t(za,θa)]}
Where arg { max [ ] } represents the output result of the corresponding grid point at the maximum value. r real represents the true horizontal distance, and s real represents the true depth.
Advantageous effects
The invention provides a weak target positioning method based on interference structure matching processing under a deep sea reliable acoustic path, which comprises the steps of firstly obtaining a plurality of frequency domain broadband beam outputs by using a single vertical array below a deep sea critical depth, splicing the plurality of frequency domain outputs in adjacent time periods in each beam output, obtaining a longer power spectrum according to the frequency domain outputs, and extracting a plurality of interference features submerged by noise by using the power spectrum obtained by splicing. And aiming at the power spectrum spliced on each wave beam, offline calculating the power spectrum of the received signal at different depths on the wave beam angle by utilizing sound field software, and carrying out matched filtering processing on the power spectrum spliced on the wave beam angle by using the simulated power spectrums at different depths to obtain the matched output maximum value at different depths. And finally, converting the distribution of the maximum value in the pitching angle-depth into the distribution in the horizontal distance-depth, and obtaining the horizontal distance and depth result of the target by searching the peak value, thereby achieving the purpose of positioning the underwater target under a lower signal-to-noise ratio.
In the invention, the single multi-element vertical array is arranged below the critical depth, so that the wide-band beam output of the vertical array frequency domain is obtained. The number of array elements of the vertical array ranges from 8 to 128, the target radiation noise is acquired by using the multi-element vertical array, and the length of a section of acquired time domain signal ranges from 60 seconds to 600 seconds. And dividing the acquired time domain signal into a plurality of subsections, wherein the time length of each subsection ranges from 4 seconds to 30 seconds, the adjacent subsections have coincidence in time, and the coincidence range is defined as the time length of the coincidence part divided by the time length of the single subsection, and the range is from 0% to 75%. The vertical array frequency domain broadband beam forming is the prior art, and each sub-segment is subjected to Fourier transformation to obtain a frequency spectrum. And carrying out broadband multi-beam processing on the frequency spectrums of all the sub-bands by using a linear array frequency domain beam forming method, and carrying out beam scanning in the pitching direction so as to obtain frequency domain broadband beam outputs at a plurality of pitching angles.
And splicing a plurality of sub-segment spectrums in the frequency domain broadband beam output of the vertical array. And carrying out modular squaring processing on the outputs of the plurality of sub-segment frequency domain broadband beams in each pitching beam to obtain a corresponding power spectrum. For each pitch beam, the power spectrums of adjacent subsections are spliced end to end, and all subsections power spectrums are connected together to obtain a longer power spectrum which is called the power spectrum of the received signal on the beam.
And then, obtaining copy power spectrums of sound sources at different positions through off-line calculation of sound field software in the prior art, and carrying out matched filtering processing on the copy power spectrums and the received signal power spectrums on each pitching wave beam to obtain a positioning result. Dividing grids on the horizontal distance and depth within the detection range (the depth is 10-500 meters, and the horizontal distance is 5-40 kilometers), and calculating the power spectrum at the geometric center of the vertical receiving array when the target is positioned on each grid point through sound field software, which is called copy power spectrum;
And respectively carrying out matched filtering processing on the received signal power spectrum on each wave beam and the copy power spectrum of each grid point, and taking the maximum value of the matched filtering output as an output result on the grid point, thereby obtaining a pitching angle-depth fuzzy graph. And calculating the corresponding relation between the pitch angle and the horizontal distance offline by utilizing sound field software, so as to determine the horizontal distance corresponding to each pitch angle. And converting the pitching angle-depth fuzzy map into a horizontal distance-depth positioning fuzzy map, and searching the peak value to obtain a positioning result.
The basic principle and the implementation scheme of the invention are verified by computer numerical simulation, and the result shows that: the weak target passive positioning method based on interference structure matching processing can estimate the target depth and horizontal distance under lower signal-to-noise ratio. The method provided by the invention can achieve the purpose of effectively estimating the target horizontal distance and depth under lower signal-to-noise ratio.
Drawings
FIG. 1 is a main step flow of the present invention;
FIG. 2 is a schematic diagram of a single vertical array receiving a horizontally moving sound source signal in a reliable sound path;
FIG. 3 is a spectrum of received signal power spectrum in a pitch angle 87 degree beam;
FIG. 4 is a spectrum of a single segment power spectrum within a pitch angle 87 degree beam;
FIG. 5 is a reliable acoustic path interference structure (signal-to-noise ratio in band-24 dB);
FIG. 6 is a graph of pitch angle-depth positioning ambiguity obtained at an in-band signal-to-noise ratio of-24 dB;
FIG. 7 is a schematic representation of the conversion from discrete grid points on the sea surface to pitch-distance coordinate links;
FIG. 8 is a horizontal distance-depth localization blur map obtained at an in-band signal-to-noise ratio of-24 dB, with the crosses representing the true sound source locations;
FIG. 9 is a depth slice of FIG. 8 at a distance of 21km (true distance);
Detailed Description
The invention will now be further described with reference to examples, figures:
the technical scheme adopted by the invention for solving the existing problems can be divided into the following steps:
1) The MIMO sonar array type and orthogonal waveform which can be used for high-resolution three-dimensional forward imaging are designed. The matrix and the orthogonal waveforms. The MIMO sonar array type consists of 2 transmitting transducers, M receiving ULA. Wherein the number M of ULA is more than or equal to 3, and the number N of hydrophones in each ULA is more than or equal to 8. The 2-element ULA and M receiving ULA consisting of 2 transmitting transducers are parallel to each other, and the perpendicular bisectors coincide with each other. For 2 transmitting transducers, 2 orthogonal waveforms for the MIMO sonar are designed. The 2 orthogonal waveforms have the same frequency band and the same pulse width, the autocorrelation function has the same main lobe, the side lobe of the autocorrelation function is less than or equal to 0.01 times of the peak value of the main lobe of the autocorrelation function, and the peak value of the cross correlation function of the 2 orthogonal waveforms is less than or equal to 0.01 times of the peak value of the main lobe of the autocorrelation function.
2) And transmitting and collecting signals according to the designed array type and waveform. The 2 transmitting transducers simultaneously transmit designed orthogonal signals, and M receiving ULA synchronously acquire echoes of a target scene.
3) Horizontal processing is performed. And carrying out matched filtering processing on the echoes on the M receiving ULA to obtain M groups of matched filtering outputs, wherein each group comprises 2N matched filtering outputs. And carrying out multi-beam processing on 2N matched filtering outputs in each group by adopting conventional beam forming according to a weighting mode of the 2N ULA, so as to obtain M groups of horizontal multi-beam outputs, wherein each group comprises Q horizontal beams.
4) And performing vertical processing. The horizontal beam outputs having the same horizontal beam angle are divided into groups, each group having M inputs in total, and the number of groups being Q, as inputs to the vertical processing. Each set of inputs is processed using a high resolution spatial spectrum estimation algorithm to obtain a vertical imaging result.
5) And combining the horizontal processing result and the vertical processing result to obtain a final high-resolution three-dimensional forward-looking imaging result.
Each step of the present invention is described in detail below:
Step 1) mainly involves vertical array frequency domain conventional beamforming. The specific contents are as follows:
The method comprises the steps of collecting target radiation noise by a multi-element vertical receiving array, dividing the collected signal into M subsections according to time, carrying out Fourier transform on each subsection, and obtaining M subsections of frequency spectrums, wherein the M subsections are represented as follows:
Kmfl＝[x1,m fl,x2,m fl,x3,m fl,...,xN,m fl]T (1)
Wherein, K m(fl) is the M (m=1, 2, M) the value at the mid-frequency point f l in the sub-band spectrum, x nm(fl) represents the value of the N (n=1, 2, N) values at frequency point f l in the M-th sub-band spectrum of array elements, N being the number of array elements, [ ] T represents transpose.
And carrying out frequency domain conventional broadband beam forming on the multi-section frequency spectrum on the vertical array by using a linear array frequency domain beam forming method. The beam sweep is performed in the elevation direction to obtain frequency domain broadband beam outputs over a plurality of elevation angles. The beam output can be expressed as:
pm(fl,θ)＝[w(fl,θ)]HKm(fl) (2)
Wherein p m(fl, θ) represents the beam output with a beam scan pitch angle θ and a frequency f l in the m-th spectrum, w (f l,θ)＝[1,eikdcosθ,ei2kdcosθ,...,ei(N-1)kdcosθ]T is a weighting vector for conventional beam forming, [ ] H represents conjugate transpose, d is an array element spacing, k=2pi f l/c0 is a wave number, and c 0 is a reference sound velocity used by the beam former.
The m-th sub-segment beam output spectrum with steering angle θ can be expressed as:
pm(θ)＝[pm(f1,θ),pm(f2,θ),...,pm(fL,θ)]T,
Where L represents the number of frequency points.
Step 2) mainly involves the splicing of the vertical array frequency domain broadband beam outputs. The specific contents are as follows:
After obtaining a plurality of sections of frequency spectrums through the step 1), multiplying conjugate vectors of the output points of the broadband beams of the plurality of sections of frequency domains on each pitching angle to obtain a plurality of sections of power spectrums.
Sm(θ)＝pm(θ)⊙pm *(θ)＝[pm *(f1,θ),pm *(f2,θ),...,pm *(fL,θ)]T,(4)
Wherein S m (θ) represents the output power spectrum with the m-th sub-segment beam scan pitch angle θ, and by-represents the dot product. And splicing a plurality of power spectrums of adjacent time periods, thereby obtaining a longer power spectrum. Expressed in S (θ):
S(θ)＝[p1(θ)T,p2(θ)T,...,pM(θ)T]T， (5)
Which is referred to as the received signal power spectrum on that beam.
Step 3) mainly relates to modeling of copy power spectrum of each grid point, and matched filtering processing of the received signal power spectrum and copy power spectrum on each wave beam, and the specific contents are as follows:
And uniformly dividing grids in the horizontal distance and depth direction in the detection range. Consider the coherent superposition of the direct wave and the sea surface reflected wave. The ideal received power spectrum is:
H(f)＝|h(f)|2(1-ej(2πΔτ)f)， (6)
Where f is the frequency, H (f) is the ideal received power spectrum, H (f) is the received signal spectrum, and Δτ is the difference in the direct wave and sea surface reflected wave time delays. When the sound field software calculates that the target is positioned on each grid point, the time delay difference delta tau at the geometric center of the vertical receiving array is calculated, the frequency band range is the same in the received signal, and the power spectrum of each grid point copy can be obtained by taking the same received signal into formula (6).
The cost function is:
Wherein H (f, theta, z a) is a copy power spectrum calculated by sound field software under the assumption of target depth z a and pitch angle theta a, The matched filtering processing is performed on A by using B and the maximum value is output. The result of the output at this grid point is t (z a,θa), thereby obtaining a vertical angle-depth blur map.
And step 4) mainly relates to offline calculation of the corresponding relation between the pitch angle and the horizontal distance by utilizing sound field software, conversion of the pitch angle-depth fuzzy map into a horizontal distance-depth positioning fuzzy map, and peak value searching to obtain a positioning result. The specific contents are as follows:
Taking any depth in the detection range, dividing the horizontal distance in the detection range, and calculating the pitch angle average value theta of the direct wave and the sea surface reflected wave at the geometric center of the vertical receiving array when the target is positioned at each horizontal distance grid through sound field software in an off-line mode, so that the corresponding relation between the pitch angle and the horizontal distance is obtained, namely:
where θ d represents the pitch angle of the direct wave and θ sr represents the pitch angle of the sea surface reflected wave.
And converting the pitching angle into horizontal depth according to the corresponding relation between the pitching angle and the horizontal distance, thereby obtaining a horizontal distance-depth positioning blur map, and outputting a result of t (z a,ra) at each grid point. Finally, obtaining a positioning result through searching the peak value, namely:
(rreal,sreal)＝arg{max[t(za,θa)]}。 (9)
Where arg { max [ ] } represents the output result of the corresponding grid point at the maximum value. r real represents the true horizontal distance, and s real represents the true depth.
The positioning result of the method provided by the invention is given through computer numerical simulation, and a flow chart of main steps of the method is shown in figure 1.
Specific implementation example:
Taking a typical deep sea environment as an example, an embodiment of the present invention is given. The implementation example uses a computer to carry out numerical simulation to test the effect of the method provided by the invention.
1) RAP environment
Assuming a sea depth of 5000 meters, the sound velocity profile is MUNK meters and the critical depth is 3700 meters.
2) Transducer parameters
The receiving array is a uniform vertical linear array, the array element depth 4200-4246.5 m, the array element distance is 1.5 m, and the number of the array elements is 32.
3) Simulating a transmitted signal and a received signal
Assuming that the depth of the target sound source is 100 meters, the distance is from 21 km to 22 km, and the vertical array receives the horizontal motion sound source signal under the reliable sound path, as shown in the schematic diagram (1). The frequency band of the underwater target radiation signal is assumed to be in the range of 200Hz-500Hz. The signal is obtained from white gaussian noise through a band-pass filter during simulation. The in-band received signal-to-noise ratio on a single hydrophone is set to-24 dB. And obtaining a transfer function according to the sound field software to obtain a receiving signal.
And acquiring a section of received signal by using the hydrophone array, and processing the section of signal to obtain a positioning result. Received signal length, number of sub-segments, sub-segment overlap ratio, and sub-segment length
The received signal is divided into 31 sub-segments in the time domain and fourier transformed to obtain 31 sub-segment sum spectra. And carrying out frequency domain conventional broadband beam forming on the multi-section frequency spectrum on the vertical array by using a linear array frequency domain beam forming method. The beam scanning is carried out in the pitching direction, the scanning angle is 70-96 degrees, the scanning interval is 1 degree, and the frequency domain broadband beam output at 27 pitching angles is obtained. And processing the output power spectrum to obtain a frequency domain broadband beam output power spectrum. The pitching angle is 87 degrees, and the spectrum of the 11 th frequency domain broadband beam output power spectrum is shown in a figure (4). The reliable acoustic path interference structure at the time of noise flooding is shown in fig. 5.
4) Received signal power spectrum formed by simulation splicing
And (3) sequentially splicing 31 sections of output power spectrums on each pitch angle to obtain 27 long received signal power spectrums. The spectrum of the 18 th (pitching angle 87 degrees) output power spectrum is shown in a figure (3), and the abscissa at the box represents the time delay difference of the sea surface reflected wave and the direct wave.
5) Simulated copy power spectrum
The horizontal distance is set to be 10-35 km, the depth is set to be 10-400 m, and the grids are evenly divided in the horizontal distance and the depth. And calculating the time delay difference of the direct wave and the sea surface reflected wave when the sound source is positioned at each grid point in an off-line mode by utilizing Bellhop software, setting RAP environment parameters in the software, calculating the time delay difference of each grid point, obtaining the copy power spectrum of each grid point by utilizing the formula (6), and selecting the frequency band range to be 200-500Hz after obtaining the time delay difference.
6) On-line matched filtering processing of actual received signal power spectrum
And respectively carrying out matched filtering processing on the received signal power spectrum at each pitching angle and the copy power spectrum of each grid point, and taking the maximum value of matched filtering output as the grid point output result, thereby obtaining an angle-depth fuzzy graph. As shown in fig. 6.
7) Offline calculating the corresponding relation between the pitch angle and the horizontal distance and online converting
And (3) offline calculating the corresponding relation between the pitch angle and the horizontal distance by utilizing sound field software, wherein the corresponding relation is shown in a figure (7). Thereby determining a horizontal distance corresponding to each pitch angle. The pitch angle-depth blur map is converted into a horizontal distance-depth positioning blur map, and the conversion result is shown in a graph (8).
8) Peak search to obtain positioning results
The peak search was performed on the graph (8), and the sound source distance was 20.8km and the depth was 100m.
According to the embodiment, the weak target positioning method based on interference structure matching processing under the reliable acoustic path can extract the time delay information submerged by noise, improve the positioning performance of the weak target under the low signal-to-noise ratio, and estimate the target depth and horizontal distance under the lower signal-to-noise ratio.
The invention solves the practical problem that the sound source depth cannot be accurately estimated by the noise inundation of the multi-path interference characteristics when the passive localization receiving signal-to-noise ratio of the sound source is low, and the multi-beam output power spectrum is spliced so as to extract the multi-path interference characteristics inundated by the noise. According to the phenomenon that the propagation delay difference of the sea surface sound source direct wave and the sea surface reflected wave is sensitive along with the depth change, the characteristic that a matched filter is sensitive to frequency mismatch is utilized, and the power spectrum of a received signal and the copy power spectrum are subjected to matched filtering processing, so that sound source position information is obtained under the condition of low signal-to-noise ratio.
Claims (1)
1. A weak target positioning method based on interference structure matching processing under a deep sea reliable acoustic path is characterized by comprising the following steps:
Step 1: setting a single multi-element vertical array below a critical depth to obtain a frequency domain broadband beam output of the vertical array, and obtaining a multi-element vertical array acquisition target radiation noise, wherein the length of a section of acquired time domain signal is 60 seconds to 600 seconds;
Dividing an acquired time domain signal into M sub-segments, and carrying out Fourier transform on each sub-segment to obtain M sub-segment spectrums;
Km (fl)＝[x1,m (fl),x2,m (fl),x3,m (fl),...,xN,m (fl)]T
Wherein, K m(fl) is the M (m=1, 2, M) the value at the mid-frequency point f l in the sub-band spectrum, x nm(fl) represents the value of the N (n=1, 2, N) values at frequency point f l in the M-th sub-band spectrum of array elements, N being the number of array elements, [ ] T represents transpose;
the time length of each sub-segment ranges from 4 seconds to 30 seconds, adjacent sub-segments are overlapped in time, and the overlap ratio range is defined as the time length of an overlapped part divided by the time length of a single sub-segment, and is 0% to 75%;
Performing broadband multi-beam processing on the frequency spectrums of all sub-bands by using a linear array frequency domain beam forming method, and performing beam scanning in the pitching direction so as to obtain frequency domain broadband beam outputs at a plurality of pitching angles;
pm(fl,θ)＝[w(fl,θ)]HKm(fl)
Wherein, p m(fl, θ) represents the beam output with the beam scanning pitch angle θ and the frequency f l in the m-th section of spectrum, w (f l,θ)＝[1,eikdcosθ,ei2kdcosθ,...,ei(N-1)kdcosθ]T is the weighting vector of conventional beam forming, [ ] H represents the conjugate transpose, d is the array element spacing, k=2pi f l/c0 is the wave number, and c 0 is the reference sound velocity used by the beam former;
The m-th sub-segment beam output spectrum with steering angle θ is:
pm(θ)＝[pm(f1,θ),pm(f2,θ),...,pm(fL,θ)]T,
Wherein L represents the number of frequency points;
Step 2, splicing the output of the vertical array frequency domain broadband beam:
Multiplying conjugate vectors of the output points of the multi-section frequency domain broadband wave beams on each pitching angle to obtain multi-section power spectrums:
Sm(θ)＝pm(θ)⊙pm *(θ)＝[pm *(f1,θ),pm *(f2,θ),...,pm *(fL,θ)]T,(4)
Wherein S m (θ) represents the output power spectrum with the m-th sub-segment beam scanning pitch angle θ, and then, by;
splicing a plurality of power spectrums of adjacent time periods, thereby obtaining a longer power spectrum, denoted by S (θ), which is a power spectrum of a received signal on the beam:
S(θ)＝[p1(θ)T,p2(θ)T,...,pM(θ)T]T；
Step 3, modeling of copy power spectrum of each grid point, and matched filtering processing of the received signal power spectrum and copy power spectrum on each wave beam:
Evenly dividing grids in the horizontal distance and depth direction in the detection range, calculating the time delay difference delta tau at the geometric center of the vertical receiving array when the target is positioned on each grid point, and obtaining the copy power spectrum of each grid point when the receiving signals are the same in the frequency band range:
wherein f is frequency, H (f, theta, z a) is a copy power spectrum calculated by sound field software under the assumption of target depth z a and pitch angle theta a, Representing using B to carry out matched filtering treatment on A and outputting a maximum value;
The output result on the grid point is t (z a,θa), so that a vertical angle-depth blur map is obtained;
step 4, calculating the corresponding relation between the pitch angle and the horizontal distance offline by utilizing sound field software, converting the pitch angle-depth fuzzy map into a horizontal distance-depth positioning fuzzy map, and searching a peak value to obtain a positioning result:
Taking any depth in the detection range, dividing the horizontal distance in the detection range, and calculating the pitch angle average value theta of the direct wave and the sea surface reflected wave at the geometric center of the vertical receiving array when the target is positioned at each horizontal distance grid through sound field software in an off-line mode, so that the corresponding relation between the pitch angle and the horizontal distance is obtained:
Wherein: θ d represents the pitch angle of the direct wave, and θ sr represents the pitch angle of the sea surface reflected wave;
Converting the pitching angle into horizontal depth to obtain a horizontal distance-depth positioning blur map, wherein the output result of each grid point is t (z a,ra);
Finally, obtaining a positioning result through searching the peak value:
(rreal,sreal)＝arg{max[t(za,θa)]}
Where arg { max [ ] } represents the output result of the corresponding grid point at the maximum value, r real represents the true horizontal distance, and s real represents the true depth.
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