CN117607876B - Method and system for detecting passive sonar multi-beam narrowband signals - Google Patents
Method and system for detecting passive sonar multi-beam narrowband signals 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
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/88—Sonar systems specially adapted for specific applications
Abstract
The invention provides a method and a system for detecting passive sonar multi-beam narrowband signals, which belong to the technical field of radio detection and comprise the following steps: dividing received multi-beam time domain data into a plurality of non-overlapping sub-band data to form a multi-beam time domain segmented data set; based on ZOOM-FFT, carrying out narrow-band spectrum refined estimation on each beam data of each time period in the multi-beam time domain segmentation data set to obtain correlation difference of multi-beam narrow-band spectrums of signals of each time period, and calculating target signal energy and average noise energy of the multi-beam narrow-band spectrums of the signals of each time period to obtain a time period optimal weighting coefficient; and carrying out optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signal in each period by adopting a time-sharing optimal weighting coefficient to obtain a multi-beam optimal weighted narrowband signal. The invention increases the weight of the time period signal with strong signal to noise ratio by introducing the processing thought of time period non-uniform weighting, and improves the detection capability of the narrow-band signal.
Description
Technical Field
The invention relates to the technical field of radio signal positioning detection, in particular to a passive sonar multi-beam narrowband signal detection method and a passive sonar multi-beam narrowband signal detection system.
Background
The passive sonar is underwater detection equipment for obtaining various sonars of target parameters by receiving and processing radiation noise or sonar signals emitted by targets in water, and has better concealment performance because the passive sonar does not actively emit signals, so the passive sonar is widely adopted.
The multi-beam narrowband spectrum estimation method aims at the multi-beam narrowband spectrum estimation received by the passive sonar, is generally used for extracting underwater target line spectrum characteristics in an omni-directional mode, is further combined with target characteristic priori information to achieve target tracking and identification, can effectively avoid the problem of target missed detection caused by short target contact time and non-pickup of a tracker, and is one of effective technical approaches of the passive sonar detection and identification. The existing passive sonar multi-beam narrowband spectrum estimation method mainly carries out multi-step processing such as time-frequency transformation, frequency domain beam forming, time-frequency inverse transformation, long-time accumulated time-frequency transformation and the like on a sonar array receiving signal so as to obtain multi-beam narrowband spectrum information and realize the receiving detection of a narrowband signal.
However, the above processing method does not sufficiently consider the influence of environmental characteristics of sonar detection, particularly the fluctuation characteristics of background noise; when the frequency spectrum structure of the signal and the noise is time-varying and space-varying and inconsistent, the narrowband spectrum shows the difference of signal to noise ratio in different spaces and time, and after long-term accumulation, the uniformly weighted time-frequency conversion processing is directly used, so that the contribution of the signal component with strong signal to noise ratio to the signal detection is weakened.
Therefore, aiming at the situation that the difference of signals and noise in different time and space is not fully considered for the receiving and detection of narrowband signals in the existing processing method and the contribution difference of signal to noise ratio in different sections of the signal detection is not considered, a new passive sonar multi-beam narrowband signal detection method needs to be provided.
Disclosure of Invention
The invention provides a method and a system for detecting a passive sonar multi-beam narrowband signal, which are used for solving the defect that the detected signal cannot obviously reflect the difference of contribution of different signal to noise ratios to signals in different periods because the difference of different time spaces between the signal and the noise is not considered when the passive sonar multi-beam narrowband signal is detected in the prior art, realizing the full utilization of the characteristic of the spectrum fluctuation difference of an underwater radio signal and the noise, and improving the distinguishing and identifying of the passive sonar to a target narrowband signal.
In a first aspect, the present invention provides a passive sonar multi-beam narrowband signal detection method, including:
receiving multi-beam time domain data, dividing the multi-beam time domain data into a plurality of non-overlapping sub-band data, and forming a multi-beam time domain segmented data set;
based on ZOOM-FFT, carrying out narrow-band spectrum refined estimation on each beam data of each time period in the multi-beam time domain segmentation data set to obtain a multi-beam narrow-band spectrum of each time period signal;
according to the correlation difference between the target signal and the background noise, calculating the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signal in each period of time to obtain a time-sharing optimal weighting coefficient;
And carrying out optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signal in each time period by adopting the time-period optimal weighting coefficient to obtain a multi-beam optimal weighted narrowband signal.
According to the method for detecting the passive sonar multi-beam narrowband signals, provided by the invention, multi-beam time domain data is received, the multi-beam time domain data is divided into a plurality of non-overlapping sub-band data, and a multi-beam time domain segmented data set is formed, and the method comprises the following steps:
Acquiring the number of traversing beams and the number of beam sampling points of a beam former in the passive sonar;
Determining output time domain signals of each traversing wave beam according to the number of traversing wave beams and the number of wave beam sampling points;
According to any beam driving angle, the segmentation number obtained by rounding down and taking the even according to the ratio of the number of beam sampling points to the preset segmentation length is used for segmenting any single-beam time domain signal in the time domain signal output by each traversing beam to obtain any single-beam time domain segmentation data;
And collecting any single-beam time domain segmentation data corresponding to all the traversing beams to form the multi-beam time domain segmentation data set.
According to the method for detecting the passive sonar multi-beam narrowband signals provided by the invention, the number of the traversing beams and the number of the beam sampling points are used for determining the output time domain signals of each traversing beam, and the method comprises the following steps:
wherein, Outputting a time domain signal for each traversing beam,/>To traverse the number of beams,/>For beam sampling points,/>For/>Steering angle of each beam.
According to the method for detecting the passive sonar multi-beam narrowband signal provided by the invention, any single-beam time domain signal in the time domain signals output by each traversing beam is segmented according to any beam driving angle and the segmentation number obtained by downward rounding and even taking according to the ratio of the number of beam sampling points to the preset segmentation length, so as to obtain any single-beam time domain segmentation data, and the method comprises the following steps:
wherein, ，/>Representing any single beam time domain signal;
wherein, ，/>，/>Representing the number of segments,/>Representing a preset segment length,/>Representing a downward rounding symbol,/>And taking an even number.
According to the method for detecting the passive sonar multi-beam narrowband signal, provided by the invention, based on a ZOOM-FFT, narrowband spectrum fine estimation is carried out on each beam data of each time period in the multi-beam time domain segmentation data set, so as to obtain a multi-beam narrowband spectrum of each time period signal, and the method comprises the following steps:
step S1, for any beam data in any period in the multi-beam time domain segmented data set Proceeding withFast fourier FFT transform of points:
wherein, ，/>The corresponding frequency value is/>，Frequency interval is/>，/>Representing a spectrum bandwidth;
Step S2, determining the required frequency range of the narrow-band frequency spectrum as ，/>Representing the minimum value of the required frequency range,/>Represents the maximum value of the required frequency range, pair/>Frequency shift is carried out to ensure that the required frequency range/>Frequency shift to baseband frequency rangeObtain baseband frequency spectrum/>：
Wherein,；
Step S3, pairLow-pass filtering, filtering signals outside the target frequency band by adopting a finite length unit impulse response (FIR) filter to obtain signals/>, which only contain the target frequency band；
Step S4, according to each intervalData pairs/>Sampling to obtain downsampled data/>，Indicating the magnification;
Step S5, for Go/>FFT conversion of the points and frequency recombination are carried out, so that a refined frequency spectrum/>：
Wherein,Corresponding frequency is/>Frequency interval is/>；
Step S6, traversing each beam data, repeating the steps S1 to S5 to obtain the first beam dataMulti-beam narrowband spectrum/>, of segment time domain data。
According to the method for detecting the passive sonar multi-beam narrowband signal, provided by the invention, the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signals in each period are calculated according to the correlation difference between the target signal and the background noise to obtain the time-sharing optimal weighting coefficient, and the method comprises the following steps:
according to the autocorrelation of the target signal and noise corresponding to the same segment of data, obtaining the first The sum of the target signal and the noise energy of the segment time domain data at each frequency point is/>：
Wherein,；
Based on the uncorrelated difference of the correlation of the target signal and the noise between the data of different time periods, the methodThe segment signals are combined pairwise to form/>Group signal pair, will be/>Segment Signal and/>The segment signals being divided into groups in whichBy/>Group signal solving target signal energy is/>：
；
Based onAnd/>Calculating the average noise energy of the whole data as/>：
；
From the following componentsSubtracting/>The target signal energy for obtaining the data of each period is/>：
；
Based on maximum output signal-to-noise ratio criterion, solving the optimal weighting coefficient of each wave beam of each time period data at each frequency point as：
。
According to the method for detecting the passive sonar multi-beam narrowband signal provided by the invention, the multi-beam narrowband spectrum of the signal in each period is optimally weighted and coherently accumulated by adopting the time-sharing optimal weighting coefficient, so as to obtain the multi-beam optimal weighted narrowband signal, and the method comprises the following steps:
Based on the time-division optimal weighting coefficient Performing optimal weighted coherent accumulation on the single-beam narrowband spectrum of the signal in each period to obtain a single-beam optimal weighted narrowband signal/>：
Wherein,For each period of time,/>；
Traversing each beam angle to obtain multi-beam optimal weighted narrow-band signal：
。
In a second aspect, the present invention also provides a passive sonar multi-beam narrowband signal detection system, including:
the segmentation module is used for receiving multi-beam time domain data, dividing the multi-beam time domain data into a plurality of non-overlapping sub-band data and forming a multi-beam time domain segmentation data set;
The narrow-band spectrum estimation module is used for carrying out narrow-band spectrum refined estimation on each beam data of each time period in the multi-beam time domain segmentation data set based on ZOOM-FFT to obtain a multi-beam narrow-band spectrum of each time period signal;
The optimal weighting coefficient estimation module is used for calculating the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signal in each period according to the correlation difference between the target signal and the background noise to obtain a time-period optimal weighting coefficient;
and the accumulation module is used for carrying out optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signal in each time period by adopting the time-sharing optimal weighting coefficient to obtain a multi-beam optimal weighted narrowband signal.
In a third aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements a passive sonar multi-beam narrowband signal detection method as described in any one of the above when the program is executed.
In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a passive sonar multi-beam narrowband signal detection method as described in any of the above.
According to the method and the system for detecting the passive sonar multi-beam narrow-band signal, provided by the invention, the sonar obtains the optimal weighting coefficient according to the correlation difference between the target signal and the background noise aiming at the multi-beam narrow-band spectrum of the signal in each period obtained by processing and conversion, and the multi-beam optimal weighting narrow-band signal is obtained by increasing the weight of the signal in the period of strong signal to noise ratio by adopting a processing method of non-uniform weighting in each period, so that the detection capability of the narrow-band spectrum is greatly improved, the problems of low detection probability of the line spectrum, poor detection continuity of the line spectrum and the like, which are caused by the influence of the underwater environment when the passive sonar processes the multi-beam narrow-band spectrum, are solved, and the method has the advantages of simple implementation principle, small calculation amount and strong real-time performance, and can be widely applied to various underwater detection environments.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a passive sonar multi-beam narrowband signal detection method provided by the invention;
Fig. 2 is a second schematic flow chart of the passive sonar multi-beam narrowband signal detection method provided by the invention;
FIG. 3 is a diagram of an exemplary narrowband spectrum refinement process provided by the present invention;
FIG. 4 is a partial graph of the comparison of the multi-beam narrowband spectrum provided by the invention, wherein (a) in FIG. 4 is the direct narrowband spectrum analysis processing, and (b) in FIG. 4 is the time-division optimal weighting processing;
fig. 5 is a schematic structural diagram of a passive sonar multi-beam narrowband signal detection system provided by the invention;
fig. 6 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Aiming at the problems of low detection probability of a weak line spectrum, poor continuity of line spectrum detection and the like, which are easily influenced by uncertain marine environments such as environmental background fluctuation, target flickering, channel change and the like in the existing passive sonar multi-beam narrowband signal processing process, the invention provides a technical means such as narrow band spectrum analysis based on signal time-sharing, narrow band spectrum refined estimation based on band-selecting fast Fourier transform (ZOOM-Fast Fourier Transformation, ZOOM-FFT), optimal weighting coefficient estimation based on maximum output signal-to-noise ratio criterion, narrow band spectrum weighted coherent accumulation and the like, and provides a passive sonar multi-beam narrowband signal detection method suitable for time-sharing optimal weighting processing under complex marine background.
Fig. 1 is a schematic flow chart of a passive sonar multi-beam narrowband signal detection method provided by the invention, and as shown in fig. 1, the method includes:
Step 100: receiving multi-beam time domain data, dividing the multi-beam time domain data into a plurality of non-overlapping sub-band data, and forming a multi-beam time domain segmented data set;
Step 200: based on ZOOM-FFT, carrying out narrow-band spectrum refined estimation on each beam data of each time period in the multi-beam time domain segmentation data set to obtain a multi-beam narrow-band spectrum of each time period signal;
Step 300: according to the correlation difference between the target signal and the background noise, calculating the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signal in each period of time to obtain a time-sharing optimal weighting coefficient;
Step 400: and carrying out optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signal in each time period by adopting the time-period optimal weighting coefficient to obtain a multi-beam optimal weighted narrowband signal.
Specifically, the embodiment of the invention firstly carries out sectional processing on multi-beam time domain data to finish the refined estimation of the multi-beam narrowband spectrum of each time period signal based on ZOOM-FFT; then, according to the correlation difference between the target signal and the background noise, calculating the target signal energy and the average noise energy of each piece of segmented data, and solving to obtain a time-segment optimal weighting coefficient; and finally, carrying out optimal weighted coherent accumulation on the narrowband spectrum based on the time-sharing optimal weighting coefficient to obtain the multi-beam narrowband spectrum subjected to time-sharing optimal weighting processing.
Referring to fig. 2, after receiving multi-beam time domain data by using passive sonar, the first step performs segmentation processing on each beam time domain signal to obtain multi-beam time-period data; the second step is to carry out narrow-band spectrum refinement solution based on ZOOM-FFT on each time period data of each wave beam, including FFT conversion, frequency shift, low-pass filtering, resampling, spectrum recombination and other steps, so as to obtain narrow-band spectrums of each time period signal under each wave beam; thirdly, according to correlation characteristic differences of signals and noise, solving optimal weighting coefficients of all time periods by solving target signal and noise energy, target signal average energy and noise average energy of data of all time periods; and step four, carrying out sectional coherent accumulation on the narrow-band spectrum of each period to obtain the multi-beam narrow-band signal subjected to time-division optimal weighting processing.
The invention obtains the optimal weighting coefficient according to the correlation difference between the target signal and the background noise aiming at the multi-beam narrowband spectrum of the signals in each period obtained by processing and converting, adopts the processing method of non-uniform weighting in time intervals by utilizing the spectrum fluctuation difference characteristic information of the signals and the noise, increases the weight of the signals in the period of strong signal to noise ratio, and obtains the multi-beam optimal weighted narrowband signal, thereby greatly improving the detection capability of the narrowband spectrum, effectively solving the problems of low detection probability of the weak line spectrum, poor detection continuity of the line spectrum and the like caused by the influence of the underwater environment when the passive sonar processes the multi-beam narrowband spectrum, having the advantages of simple implementation principle, small calculation amount and strong instantaneity, and being widely applicable to various underwater detection environments.
Based on the above embodiment, step 100 in the present invention includes:
Acquiring the number of traversing beams and the number of beam sampling points of a beam former in the passive sonar;
determining each traversing wave beam output time domain signal according to the number of traversing wave beams and the number of wave beam sampling points;
According to any beam driving angle, the segmentation number obtained by downward rounding and coupling taking according to the ratio of the number of beam sampling points to the preset segmentation length is used for segmenting any single-beam time domain signal in the time domain signals output by each traversing beam, so as to obtain any single-beam time domain segmentation data;
And collecting any single-beam time domain segmentation data corresponding to all the traversing beams to form a multi-beam time domain segmentation data set.
Specifically, multi-beam time domain data received by a wave beam former in the passive sonar are segmented, and the multi-beam time domain data are set asWill/>Non-overlapping division into/>Length is/>Is used for the production of the steel wire rope,Output of each traversing beam for the beamformer,/>In order to traverse the number of beams,Is the number of sampling points.
For/>Beamforming output time domain signal under individual beams,/>For/>Steering angle of individual beams,/>The sampling time, i.e. the number of sampling points. For convenience of explanation, the embodiment of the invention performs/>, on single-beam time domain dataSegment, have/>Wherein/>，/>，/>，/>Representing a downward rounding symbol, where/>Is even.
The invention segments the received time domain signal aiming at the problem of the reduction of the line spectrum detection continuity caused by the fluctuation of the frequency spectrum of the signal and the noise in different time periods, can distinguish different segmented signals with different signal intensities and background noise, is convenient for the non-uniform weighting of the subsequent time periods, and effectively improves the line spectrum detection performance.
Based on the above embodiment, step 200 in the present invention includes:
by individual beam data for individual time periods Carrying out narrow-band spectrum refinement solution based on ZOOM-FFT to obtain multi-beam narrow-band spectrum/>, of each periodThe solving step comprises the following steps:
step S1, for any beam data in any period in the multi-beam time domain segmented data set Proceeding withFast fourier FFT transform of points:
wherein, ，/>The corresponding frequency value is/>，Frequency interval is/>，/>Representing a spectrum bandwidth;
Step S2, determining the required frequency range of the narrow-band frequency spectrum as ，/>Representing the minimum value of the required frequency range,/>Represents the maximum value of the required frequency range, pair/>Frequency shift is carried out to ensure that the required frequency range/>Frequency shift to baseband frequency rangeObtain baseband frequency spectrum/>：
Wherein,；
Step S3, pairLow-pass filtering, filtering signals outside the target frequency band by adopting a finite length unit impulse response (FIR) filter to obtain signals/>, which only contain the target frequency band；
Step S4, according to each intervalData pairs/>Sampling to obtain downsampled data/>，Indicating the magnification;
Step S5, for Go/>FFT conversion of the points and frequency recombination are carried out, so that a refined frequency spectrum/>：
Wherein,Corresponding frequency is/>Frequency interval is/>；
Step S6, traversing each beam data, repeating the steps S1 to S5 to obtain the first beam dataMulti-beam narrowband spectrum/>, of segment time domain data。
By adopting the ZOOM-FFT algorithm, the invention can improve the line spectrum identification accuracy when the time domain signal length is limited, and compared with the traditional FFT algorithm, the invention has the advantages of finer and more accurate signal processing.
Taking the simulation data shown in fig. 3 as an example, a comparison of a narrow-band spectrum refined estimation based on ZOOM-FFT with a conventional FFT narrow-band spectrum estimation is given. The simulation conditions are as follows, 4 narrowband signal frequencies are [55Hz,56Hz,59Hz,75Hz ], signal amplitude is [20,20,30,10], sampling frequency is 5000Hz, and signal duration is 1.6386s. The frequency band of interest of the ZOOM-FFT is set to 40 Hz-80 Hz, and the FFT point number is set to 2048. By comparison, under the condition that the signal length and the FFT point number are limited, the ZOOM-FFT still keeps a narrower main lobe width, signals at 55Hz,56Hz and 59Hz can be effectively identified, the method has better distinguishing degree, the resolution of the FFT is lower, and signals with similar frequencies are difficult to distinguish. The analysis shows that the ZOOM-FFT can be applied to the refinement solving process of the segmented multi-beam narrowband spectrum.
Based on the above embodiment, step 300 in the present invention includes:
according to the autocorrelation of the target signal and noise corresponding to the same segment of data, obtaining the first The sum of the target signal and the noise energy of the segment time domain data at each frequency point is/>：
Wherein,；
Based on the uncorrelated difference of the correlation of the target signal and the noise between the data of different time periods, the methodThe segment signals are combined pairwise to form/>Group signal pair, will be/>Segment Signal and/>The segment signals being divided into groups in whichBy/>Group signal solving target signal energy is/>：
；
Based onAnd/>Calculating the average noise energy of the whole data as/>：
；
From the following componentsSubtracting/>The target signal energy for obtaining the data of each period is/>：
；
Based on maximum output signal-to-noise ratio criterion, solving the optimal weighting coefficient of each wave beam of each time period data at each frequency point as：
。
According to the method, aiming at the difference of the fluctuation degree of the signals and the noise in each period, the background noise level and the signal source level of each period on the scanning frequency point and the wave beam are obtained based on the maximum output signal-to-noise ratio criterion, so that the optimal weighting coefficient is effectively solved, and the processing performance of the non-uniform weighting line spectrum detection in each period is improved.
Based on the above embodiment, step 400 in the present invention includes:
Pairs of embodiments of the invention And carrying out coherent accumulation on the narrowband spectrums of each time period to obtain passive sonar multi-beam narrowband spectrums subjected to time period optimal weighting processing.
The single-beam narrowband spectrum is used for illustration, and the final output beam narrowband spectrum is obtained by coherently accumulating the narrowband spectrum of each period through optimal weighting and time delay compensation processingI.e./>Wherein/>For each period of time,/>. Traversing each beam angle, and taking passive sonar multi-beam narrowband spectrum as/>。
The narrow-band spectrum analysis results obtained by sea test data processing shown in fig. 4 and directly subjected to narrow-band spectrum analysis (shown in (a) of fig. 4) and time-division optimal weighting processing (shown in (b) of fig. 4) are compared, the frequency range [120,140] Hz is processed, the target is positioned in a 108-degree azimuth, the contrast shows that a line spectrum with stronger energy exists at the 131Hz frequency can be detected by time-division processing, and the line spectrum energy is weakened under the average action due to the fluctuation characteristics of noise and target signals by direct processing, so that the line spectrum energy cannot be detected.
The passive sonar multi-beam narrowband signal detection system provided by the invention is described below, and the passive sonar multi-beam narrowband signal detection system described below and the passive sonar multi-beam narrowband signal detection method described above can be correspondingly referred to each other.
Fig. 5 is a schematic structural diagram of a passive sonar multi-beam narrowband signal detection system according to an embodiment of the present invention, as shown in fig. 5, including: a segmentation module 51, a narrowband spectrum estimation module 52, an optimal weighting coefficient estimation module 53, and an accumulation module 54, wherein:
The segmentation module 51 is configured to receive multi-beam time domain data, divide the multi-beam time domain data into a plurality of non-overlapping sub-band data, and form a multi-beam time domain segmented data set; the narrowband spectrum estimation module 52 is configured to perform narrowband spectrum refinement estimation on each beam data of each period in the multi-beam time domain segmentation data set based on ZOOM-FFT, so as to obtain a multi-beam narrowband spectrum of each period signal; the optimal weighting coefficient estimation module 53 is configured to calculate target signal energy and average noise energy of the multi-beam narrowband spectrum of the signal at each time interval according to a correlation difference between the target signal and background noise, so as to obtain a time interval optimal weighting coefficient; the accumulating module 54 is configured to perform optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signal in each period by using the time-sharing optimal weighting coefficient, so as to obtain a multi-beam optimal weighted narrowband signal.
Fig. 6 illustrates a physical schematic diagram of an electronic device, as shown in fig. 6, which may include: processor 610, communication interface (Communications Interface) 620, memory 630, and communication bus 640, wherein processor 610, communication interface 620, memory 630 communicate with each other via communication bus 640. Processor 610 may invoke logic instructions in memory 630 to perform a passive sonar multi-beam narrowband signal detection method comprising: receiving multi-beam time domain data, dividing the multi-beam time domain data into a plurality of non-overlapping sub-band data, and forming a multi-beam time domain segmented data set; based on ZOOM-FFT, carrying out narrow-band spectrum refined estimation on each beam data of each time period in the multi-beam time domain segmentation data set to obtain a multi-beam narrow-band spectrum of each time period signal; according to the correlation difference between the target signal and the background noise, calculating the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signal in each period of time to obtain a time-sharing optimal weighting coefficient; and carrying out optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signal in each time period by adopting the time-period optimal weighting coefficient to obtain a multi-beam optimal weighted narrowband signal.
Further, the logic instructions in the memory 630 may be implemented in the form of software functional units and stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a read-only memory (ROM), a random access memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the passive sonar multi-beam narrowband signal detection method provided by the above methods, the method comprising: receiving multi-beam time domain data, dividing the multi-beam time domain data into a plurality of non-overlapping sub-band data, and forming a multi-beam time domain segmented data set; based on ZOOM-FFT, carrying out narrow-band spectrum refined estimation on each beam data of each time period in the multi-beam time domain segmentation data set to obtain a multi-beam narrow-band spectrum of each time period signal; according to the correlation difference between the target signal and the background noise, calculating the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signal in each period of time to obtain a time-sharing optimal weighting coefficient; and carrying out optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signal in each time period by adopting the time-period optimal weighting coefficient to obtain a multi-beam optimal weighted narrowband signal.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. The method for detecting the passive sonar multi-beam narrowband signal is characterized by comprising the following steps of:
receiving multi-beam time domain data, dividing the multi-beam time domain data into a plurality of non-overlapping sub-band data, and forming a multi-beam time domain segmented data set;
carrying out narrow-band spectrum refined estimation on each beam data of each time period in the multi-beam time domain segmentation data set based on band selection fast Fourier transform ZOOM-FFT to obtain a multi-beam narrow-band spectrum of each time period signal;
according to the correlation difference between the target signal and the background noise, calculating the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signal in each period of time to obtain a time-sharing optimal weighting coefficient;
Performing optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signals in each time period by adopting the optimal weighting coefficient in each time period to obtain a multi-beam optimal weighted narrowband signal;
According to the correlation difference between the target signal and the background noise, calculating the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signal in each period to obtain a time-division optimal weighting coefficient, wherein the method comprises the following steps:
according to the autocorrelation of the target signal and noise corresponding to the same segment of data, obtaining the first The sum of the target signal and the noise energy of the segment time domain data at each frequency point is/>：
Wherein,；
Based on the uncorrelated difference of the correlation of the target signal and the noise between the data of different time periods, the methodThe segment signals are combined pairwise to form/>Group signal pair, will be/>Segment Signal and/>The segment signals are divided into a group, wherein/>By/>Group signal solving target signal energy is/>：
；
Based onAnd/>Calculating the average noise energy of the whole data as/>：
；
From the following componentsSubtracting/>The target signal energy for obtaining the data of each period is/>：
；
Based on maximum output signal-to-noise ratio criterion, solving the optimal weighting coefficient of each wave beam of each time period data at each frequency point as：
。
2. The method for detecting a passive sonar multi-beam narrowband signal according to claim 1, wherein receiving multi-beam time domain data, dividing the multi-beam time domain data into a plurality of non-overlapping sub-segment data, forming a multi-beam time domain segmented data set, comprises:
Acquiring the number of traversing beams and the number of beam sampling points of a beam former in the passive sonar;
Determining output time domain signals of each traversing wave beam according to the number of traversing wave beams and the number of wave beam sampling points;
According to any beam driving angle, the segmentation number obtained by rounding down and taking the even according to the ratio of the number of beam sampling points to the preset segmentation length is used for segmenting any single-beam time domain signal in the time domain signal output by each traversing beam to obtain any single-beam time domain segmentation data;
And collecting any single-beam time domain segmentation data corresponding to all the traversing beams to form the multi-beam time domain segmentation data set.
3. The passive sonar multi-beam narrowband signal detection method of claim 2, wherein determining each of the traversal beam output time domain signals from the number of traversal beams and the number of beam sample points comprises:
wherein, Outputting a time domain signal for each traversing beam,/>To traverse the number of beams,/>For beam sampling points,/>For/>Steering angle of each beam.
4. The method for detecting passive sonar multi-beam narrowband signals according to claim 2, wherein the step of segmenting any single-beam time domain signal in the output time domain signal of each traversing beam according to any beam driving angle and the number of segments obtained by rounding down and taking the even according to the ratio of the number of beam sampling points to the preset segment length, includes:
wherein, ，/>Representing any single beam time domain signal;
wherein, ，/>，/>Representing the number of segments,/>Representing a preset segment length,/>Representing a downward rounding symbol,/>And taking an even number.
5. The method for detecting a passive sonar multi-beam narrowband signal according to claim 1, wherein based on a ZOOM-FFT, performing narrowband spectrum refinement estimation on each beam data of each period in the multi-beam time domain segmented data set to obtain a multi-beam narrowband spectrum of each period signal, comprising:
step S1, for any beam data in any period in the multi-beam time domain segmented data set Go/>Fast fourier FFT transform of points:
wherein, ，/>The corresponding frequency value is/>，/>Frequency interval is/>，/>Representing a spectrum bandwidth;
Step S2, determining the required frequency range of the narrow-band frequency spectrum as ，/>Representing the minimum value of the required frequency range,/>Represents the maximum value of the required frequency range, pair/>Frequency shift is carried out to ensure that the required frequency range/>Frequency shift to baseband frequency rangeObtain baseband frequency spectrum/>：
Wherein,；
Step S3, pairLow-pass filtering, filtering signals outside the target frequency band by adopting a finite length unit impulse response (FIR) filter to obtain signals/>, which only contain the target frequency band；
Step S4, according to each intervalData pairs/>Sampling to obtain downsampled data/>，Indicating the magnification;
Step S5, for Go/>FFT conversion of the points and frequency recombination are carried out, and a refined frequency spectrum can be obtained：
Wherein,Corresponding frequency is/>Frequency interval is/>；
Step S6, traversing each beam data, repeating the steps S1 to S5 to obtain the first beam dataMulti-beam narrowband spectrum/>, of segment time domain data。
6. The method for detecting a multi-beam narrowband signal of a passive sonar according to claim 5, wherein performing optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signal in each period by using the time-division optimal weighting coefficient to obtain a multi-beam optimal weighted narrowband signal comprises:
Based on the time-division optimal weighting coefficient Performing optimal weighted coherent accumulation on the single-beam narrowband spectrum of the signal in each period to obtain a single-beam optimal weighted narrowband signal/>：
Wherein,For each period of time,/>；
Traversing each beam angle to obtain multi-beam optimal weighted narrow-band signal：
。
7. A passive sonar multi-beam narrowband signal detection system, comprising:
the segmentation module is used for receiving multi-beam time domain data, dividing the multi-beam time domain data into a plurality of non-overlapping sub-band data and forming a multi-beam time domain segmentation data set;
The narrow-band spectrum estimation module is used for carrying out narrow-band spectrum refined estimation on each beam data of each time period in the multi-beam time domain segmentation data set based on ZOOM-FFT to obtain a multi-beam narrow-band spectrum of each time period signal;
The optimal weighting coefficient estimation module is used for calculating the target signal energy and the average noise energy of the multi-beam narrowband spectrum of the signal in each period according to the correlation difference between the target signal and the background noise to obtain a time-period optimal weighting coefficient;
The accumulation module is used for carrying out optimal weighted coherent accumulation on the multi-beam narrowband spectrum of the signals in each time period by adopting the optimal weighting coefficient in each time period to obtain a multi-beam optimal weighted narrowband signal;
the optimal weighting coefficient estimation module is specifically configured to:
according to the autocorrelation of the target signal and noise corresponding to the same segment of data, obtaining the first The sum of the target signal and the noise energy of the segment time domain data at each frequency point is/>：
Wherein,；
Based on the uncorrelated difference of the correlation of the target signal and the noise between the data of different time periods, the methodThe segment signals are combined pairwise to form/>Group signal pair, will be/>Segment Signal and/>The segment signals are divided into a group, wherein/>By/>Group signal solving target signal energy is/>：
；
Based onAnd/>Calculating the average noise energy of the whole data as/>：
；
From the following componentsSubtracting/>The target signal energy for obtaining the data of each period is/>：
；
Based on maximum output signal-to-noise ratio criterion, solving the optimal weighting coefficient of each wave beam of each time period data at each frequency point as：
。
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the passive sonar multi-beam narrowband signal detection method of any of claims 1 to 6 when the program is executed by the processor.
9. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements a passive sonar multi-beam narrowband signal detection method as defined in any of claims 1 to 6.
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