CN108088547A - A kind of weak target passive detection method based on small-bore two-dimensional vector hydrophone battle array - Google Patents
A kind of weak target passive detection method based on small-bore two-dimensional vector hydrophone battle array Download PDFInfo
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Abstract
The invention discloses a kind of weak target passive detection methods of small-bore two-dimensional vector hydrophone battle array.This method utilizes the reception data of small-bore two-dimensional vector hydrophone battle array, first calculate central spot acoustic pressure (1 passage), vibration velocity (2 passage), vibration velocity transverse direction difference (2 passage) and vibration velocity longitudinal direction difference (2 passage), above-mentioned 7 channel data covariance matrixes are calculated again, it is scanned using accurate direction vector, the output spatial spectrum of array is calculated, finally detects whether that there are targets using the average for normalizing spatial spectrum.This method takes full advantage of vibration velocity and the directive property of vibration velocity difference value, and the spatial spectrum of small-bore two-dimensional vector hydrophone battle array is calculated using accurate direction vector, reduces the detectable signal-to-noise ratio of target, improves the effective detection range of small-bore two-dimensional vector hydrophone battle array.The method of the present invention can be applied in buoy, subsurface buoy, fish finder, submarine navigation device, Underwater Navigation and navigation etc. in products, have larger potential using value.
Description
Technical Field
The invention relates to a passive detection method of a small-aperture two-dimensional vector hydrophone array weak target, in particular to a method for calculating an output space spectrum by utilizing sound pressure at the central point of a closely-placed two-dimensional vector hydrophone array, two orthogonal vibration velocity components and four vibration velocity difference components and then utilizing the average value of a normalized space spectrum to detect a target.
Background
The vector hydrophone can acquire more comprehensive sound field information, and the detection capability of the sonar system can be improved by the dipole directivity of which the vibration speed is independent of the frequency and the characteristic of the acoustic energy flow processor for inhibiting isotropic noise. In a low frequency range, the vector hydrophone has the advantages of small volume, light weight, convenience in arrangement and the like compared with a sound pressure array. In recent years, vector hydrophones have found widespread use in sonobuoys, submerged buoys, seismic monitoring systems, and noise measurement systems.
In order to obtain a hydrophone with better performance, a plurality of scholars carry out series research on the vibration velocity gradient hydrophone, and theoretical analysis and real-field experiments prove that the vibration velocity gradient hydrophone can obtain better directivity compared with a vector hydrophone. The vibration velocity gradient hydrophone is essentially a composite sensor array (small aperture vector array) formed by closely placing vector hydrophones, and in order to obtain more accurate directivity, the distance between diagonal vector array elements of the vibration velocity gradient hydrophone must be small enough. As the array element spacing increases, the approximation error increases. When the receiving signal-to-noise ratio is high, a target space spectrum can be obtained by utilizing the preprocessing of the multidimensional output of the vibration velocity gradient hydrophone, and the direction of the target can be estimated through peak value searching. When the receiving signal-to-noise ratio is low, the performance of the output spatial spectrum of the vibration velocity gradient hydrophone is poor, and the direction of the target cannot be correctly estimated by using the output spatial spectrum. In engineering, the system usually works in a wider frequency band range, so the spacing between the vibration velocity gradient hydrophones usually does not meet the approximate limitation condition of the vibration velocity gradient hydrophone (the limitation condition is that the diagonal array element spacing is less than 0.2 times of the working wavelength, and the vibration velocity gradient hydrophone which does not meet the limitation condition is called a small-aperture vector hydrophone array in the patent), so the spatial spectrum performance of the system is more seriously degraded.
If a processing method or technology is available, the spatial spectrum characteristic of the small-aperture vector array at the time of low signal-to-noise ratio can be improved, and the output spatial spectrum of the small-aperture vector array can be utilized to realize the passive detection of the weak target, the technology will inevitably expand the application range of the small-aperture vector hydrophone array, especially the application in a small-aperture sonar detection system.
Disclosure of Invention
The purpose of the invention is: the passive detection method for the weak target of the small-aperture vector hydrophone array is simple, practical, stable and reliable by adopting the processing idea of the vibration velocity gradient hydrophone, utilizing the optimized space spectrum of the small-aperture vector hydrophone array and taking the average value of the output normalized space spectrum as the test statistic.
The technical scheme of the invention is as follows: a weak target passive detection method based on a small-aperture two-dimensional vector hydrophone array is disclosed. The method comprises the following steps:
(1) Receiving data p of 12 channels of a two-dimensional vector hydrophone array with diagonal arrangement (four array elements are respectively arranged at four corners of a rectangle) i (n)、v xi (n)、v yi (n) (i =1,2,3,4, which indicates array element number, and n indicates data sample point number), and is converted into a complex signal by hilbert conversion
(2) Complex sound pressure signals to four channelsAveraging to obtain the sound pressure signal at the central point of the vector hydrophone arrayFor four channels of complex vibration speed signalsAveraging, and calculating the vibration velocity in the x-axis direction at the central point of the vector hydrophone arrayFor four channels of complex vibration speed signalsAveraging, and finding the central point of the vector hydrophone arrayy-axis direction vibration velocity
(3) Using eight-channel complex vibration speed signalRespectively solving the differential component of the transverse vibration velocity at the central point of the vector hydrophone arrayAnd differential component of longitudinal vibration velocityThen phase-shifting it by 90 DEG to obtain
(4) The data obtained in the steps (2) and (3) are arranged together to obtain the output of the small-aperture two-dimensional vector hydrophone arrayThen, the data covariance matrix of the two-dimensional vector hydrophone array is solvedThe matrix is a 7 x 7 complex symmetric matrix, where N represents the number of data sample samples.
(5) According to the array size of the vector hydrophone array and the system working frequency band, the accurate direction vector of the two-dimensional vector hydrophone array is calculated by the following formula "
Where θ represents the scan preset angle, λ represents the wavelength of the signal, and Δ x represents the separation between diagonal vector hydrophones.
(6) Utilizing the accurate direction vector U in the step (5) I (theta) and the data covariance matrix in step (4)Calculating the spatial spectrum, and then solving the mean value of the normalized spatial spectrum to obtain spatial spectrum test statistic
Where M represents the number of spatial angle samples, θ m Representing the mth spatial scan angle value.
(7) Maximum false alarm probability P according to system requirements f And (5) calculating a detection threshold value D by using the spatial spectrum test statistic formula in the step (6) and a Monte Carlo statistical method according to the covariance matrix of the environmental noise data th (N,M)。
(8) Calculating D (N, M) in real time by using the acquired data, and comparing D (N, M) with D th (N, M) are compared, if D (N, M)<D th (N, M), then the target is present, otherwise the target is absent.
The invention has the beneficial effects that the invention provides a passive target detection method based on a small-aperture vector hydrophone array with stability and low signal-to-noise ratio, according to the received data of the vector hydrophone array, the sound pressure (1 channel), the vibration speed (2 channels), the vibration speed transverse difference (2 channels) and the vibration speed longitudinal difference (2 channels) at the central point are calculated, the covariance matrix of the output data of the 7 channels is calculated, then the accurate direction vector is utilized to scan, the output space spectrum of the array is calculated, and the average value of the normalized space spectrum is utilized to detect whether the passive target exists. The invention fully utilizes the directivity of sound pressure, vibration velocity and vibration velocity difference values and the correlation characteristics of noise signal sound pressure, vibration velocity and vibration velocity difference information, and utilizes the accurate direction vector to calculate the space spectrum of the array, thereby reducing the detectable signal-to-noise ratio of the passive target and further improving the effective detection distance of the passive target. The method can be applied to products such as buoys, submerged buoys, fish finders, underwater vehicles, underwater positioning and navigation and the like, and has a great potential application value.
Drawings
FIG. 1: the small aperture two-dimensional vector hydrophone array structure is schematic.
FIG. 2: and a small-aperture two-dimensional vector hydrophone array passive target space spectrum detection signal processing block diagram.
FIG. 3: the diagonal array element spacing delta x =0.4m of the small-aperture two-dimensional vector hydrophone array, the target signal is CW pulse, and the central frequency f 0 =1kHz, the system sampling frequency is f s ＝8f 0 Noise is numerically simulated isotropic noise, systematic ground false alarm probability P f =0.05, and a probability statistical result graph of detection success of the small-aperture two-dimensional vector hydrophone array spatial spectrum detector when the target is at 60 ° azimuth.
FIG. 4: the small-aperture two-dimensional vector hydrophone array diagonal array element interval delta x =0.4m, a target signal is a CW pulse, and the center frequency f 0 =1kHz, the system sampling frequency is f s ＝8f 0 Noise is numerically simulated isotropic noise, systematic ground false alarm probability P f And =0.05, when the target is in the 45-degree direction, a detection success probability statistical result chart of the small-aperture two-dimensional vector hydrophone array spatial spectrum detector.
Detailed Description
The invention will now be further described with reference to the following examples and drawings:
the structure of the small-aperture two-dimensional vector hydrophone array is shown in fig. 1 and consists of four vector hydrophones which are diagonally distributed. The invention calculates the sound pressure, the vibration velocity, the transverse vibration velocity difference and the longitudinal vibration velocity difference information at the central point by utilizing the average operation of the output sound pressure of four diagonal vector hydrophones and the average and difference operation of the output vibration velocity components, calculates the output space spectrum by accurate direction vector scanning, and detects whether a target exists by utilizing the average value of the normalized space spectrum, wherein the signal processing flow is shown in figure 2.
In this embodiment, the method for passively detecting a weak target based on a small-aperture two-dimensional vector hydrophone array includes the following steps:
the method comprises the following steps: respectively using p as received data of 12 channels of two-dimensional vector hydrophone array i (n)、v xi (n)、v yi (n) (i =1,2,3,4 indicating the array element number, and n indicating the sampling point number of the signal), and converted into complex signals by a hilbert converter
Step two: combining the complex sound pressure signals of four channels(i =1,2,3,4) and divided by 2 to obtain the sound pressure signal at the center point of the vector hydrophone array
Step three: the four channels are subjected to complex vibration velocity signals(i =1,2,3,4), and dividing by 2 to obtain the vibration velocity of vector hydrophone array at the central point in the x-axis direction
Step four: the four channels are subjected to complex vibration velocity signals(i =1,2,3,4) and dividing by 2 to obtain the vibration velocity of the vector hydrophone array at the center point in the y-axis direction
Step five: complex oscillation speed signal using 1,2 array elements (two vector array elements on horizontal axis of fig. 1)Differential value of vibration velocityPhase shift of-90 DEG
Step six: complex oscillation speed signal using 3,4 array elements (two vector array elements on vertical axis of fig. 1)Differential value of vibration velocityPhase shift of-90 DEG
Step seven: complex oscillation speed signal using 3,4 array elements (two vector array elements on vertical axis of fig. 1)Find outThen phase shift is carried out by 90 degrees to obtain
Step eight: complex oscillation speed signal using 1,2 array elements (two vector array elements on horizontal axis of fig. 1)Find outThen phase shift is carried out by 90 degrees to obtain
Step nine: arranging the data obtained in the second step to the eighth step together to obtain the 7-dimensional output vector of the small aperture vector array(symbol "T" represents the transpose of the matrix) to solve the covariance matrix of the output of the small aperture vector hydrophone array(the symbol "H" represents the conjugate transpose of the matrix), which is a 7 × 7 complex symmetric matrix.
Step ten: according to the array configuration of the vector hydrophone array and the system working frequency band, the following formula is utilized to calculate the 'accurate direction vector' of the small-aperture vector array "
Where θ represents the scan preset angle, λ represents the wavelength of the signal, and Δ x represents the spacing between diagonal vector hydrophones.
Step eleven: 'accurate direction vector' U output by using small aperture vector array I (θ m ) Scanning is carried out by adopting a formulaA spatial beam spectrum is calculated.
Step twelve: calculating the normalized value of the spatial spectrum, and then averaging to obtain the spatial spectrum test statistic
Where M represents the number of spatial angle samples, N represents the number of data sample samples, θ m Representing the mth spatial scan angle value.
Step thirteen: maximum false alarm probability P according to system requirements f And the above mentioned testsTesting statistic D (N, M), and counting detection threshold D by Monte Carlo method in noise environment th (N,M)；
Fourteen steps: calculating D (N, M) in real time, and comparing D (N, M) with D th (N, M) if D (N, M)<D th (N, M), then the target is present, otherwise the target is absent.
Based on the array structure shown in fig. 1, the signal processing method shown in fig. 2 is adopted, and the present invention provides an embodiment: and when the distance between the diagonal array elements of the small-aperture two-dimensional vector hydrophone is 0.4m and the working center frequency is 1kHz, calculating the detection probability under the conditions of different signal-to-noise ratios by utilizing the calculating steps and adopting a Monte Carlo statistical method. Fig. 3 shows the result of detection using the beam spectrum formed by conventional beam forming when the target is at 60 ° azimuth (the incident direction is at 60 ° to the positive half axis of the x-axis in fig. 2). The circular dotted line in the figure is a detection probability curve of the method of the invention, and the diamond solid line is a detection probability curve obtained by carrying out detection statistics by using a beam spectrum formed by a conventional weight vector beam. Fig. 4 shows the results of detection using the beam spectrum of conventional beam forming when the target is at a 45 ° azimuth (the incident direction is at 45 ° to the positive half-axis of the x-axis in fig. 2). The circular dotted line in the figure is a detection probability curve of the method of the invention, and the diamond solid line is a detection probability curve obtained by carrying out detection statistics by using a beam spectrum formed by a conventional weight vector beam. As can be seen from the curves in fig. 3 and 4, the detectable signal-to-noise ratio of the method of the present invention is reduced by 2dB compared to the conventional processing method. The method has better detection performance at low signal-to-noise ratio, can improve the effective detection distance of the sonar system, and expands the working frequency band of the system.
The invention is of course also capable of other embodiments and modifications will occur to those skilled in the art in light of the disclosure and it is intended to cover such modifications as fall within the scope of the appended claims.
Claims (1)
1. A weak target passive detection method based on a small-aperture two-dimensional vector hydrophone array is disclosed. The method comprises the following steps:
(1) Receiving data p of 12 channels of a two-dimensional vector hydrophone array with diagonal arrangement (four array elements are respectively arranged at four corners of a rectangle) i (n)、v xi (n)、v yi (n) (i =1,2,3,4, which indicates array element number, and n indicates data sample point number), and is converted into a complex signal by hilbert conversion
(2) Complex sound pressure signals to four channelsAveraging to obtain the sound pressure signal at the central point of the vector hydrophone arrayFor four channels of complex vibration speed signalsAveraging, and calculating the vibration velocity in the x-axis direction at the central point of the vector hydrophone arrayFor four channels of complex vibration speed signalsAveraging, and calculating the vibration velocity in the y-axis direction at the central point of the vector hydrophone array
(3) Using eight channel complex vibration speed signalsRespectively solving the differential component of the transverse vibration velocity at the central point of the vector hydrophone arrayAnd differential component of longitudinal vibration velocityThen phase-shifting it by 90 DEG to obtain
(4) Arranging the data obtained in the steps (2) and (3) together to obtain the output of the small-aperture two-dimensional vector hydrophone arrayThen solving the data covariance matrix of the two-dimensional vector hydrophone arrayThe matrix is a 7 x 7 complex symmetric matrix, where N represents the number of data sample samples;
(5) According to the array size of the vector hydrophone array and the system working frequency band, the accurate direction vector of the two-dimensional vector hydrophone array is calculated by the following formula "
Wherein theta represents a scanning preset angle, lambda represents the wavelength of a signal, and deltax represents the distance between diagonal vector hydrophones;
(6) Using the accurate direction vector U in step (5) I (theta) and the data covariance matrix in step (4)Calculating the spatial spectrum, and then solving the mean value of the normalized spatial spectrum to obtain spatial spectrum test statistic
Where M represents the number of spatial angle samples, θ m Representing the mth spatial scan angle value;
(7) Maximum false alarm probability P according to system requirements f And (4) calculating a detection threshold value D by using the spatial spectrum test statistic formula in the step (6) and a Monte Carlo statistical method according to the covariance matrix of the environmental noise data th (N,M)；
(8) Calculating D (N, M) in real time by using the acquired data, and comparing D (N, M) with D th (N, M) if D (N, M)<D th (N, M), then the target is present, otherwise the target is absent.
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