Simulation system passive linear array sonar array element level signal output method

Abstract

The invention provides a passive linear array sonar array element level signal output method of a simulation system. The method comprises the following steps: setting parameters; generating a passive target source signal with a high sampling rate; calculating the signal receiving time delay of each hydrophone according to the orientation; simulating and generating each hydrophone to receive a target signal; marine environment background noise received by each hydrophone is simulated and generated; the analog signal, the analog noise and the actual array data are superposed to generate full-array element data; fourier transform and frequency domain beam forming are carried out on the time domain array element level data to obtain a passive space energy spectrum; and carrying out long-time accumulation on the multi-beam time domain data, and carrying out Fourier transform to obtain a multi-beam narrow-band Lofar. The method has the beneficial effects that linear array simulation data and actually measured array data in an ideal scene are fused, a playback function is achieved, and original array data redisk is supported. On the basis, an underwater acoustic target, noise and interference are added, array sample data are output, and trainees are supported to carry out training and assessment such as passive warning detection and target tracking.

Description

Technical Field

[0001] The present invention relates to the technical field of linear array sonar, and mainly relates to a method for outputting signals at the element level of a passive linear array sonar in a simulation system. Background Art

[0002] How to quickly form combat capabilities of linear array sonar has always been the focus of attention of naval organs at all levels. Closely focusing on this requirement, the present invention designs a set of passive linear array sonar element-level simulation training system, which can effectively support naval forces and scientific research institutions to carry out teaching, training and other tasks of linear array sonar, help trainees master the technical principles and operation methods of sonar equipment proficiently, quickly improve the professional technical level of trainees, and provide strong support for giving full play to the combat effectiveness of linear array sonar.

[0003] There are mainly two ways for existing linear array sonar simulation training systems. One is to playback the original array data recorded in the database and obtain target feature information through signal processing at the element level. This method is also called data review, and the sonar detection efficiency in the real scenario can be obtained intuitively. The other method is to carry out target simulation based on the in-machine simulator. The principle is mainly to approximate by constructing corresponding mathematical models according to the characteristics of actual underwater targets, ocean ambient noise radiation, and ocean sound propagation, and then simulate and output array data based on the signal processing process at the element level. This type of method is mainly used to test the overall performance of the sonar system.

[0004] Using the data playback method to carry out sonar simulation training is mainly to complete the processing and display of warning detection, target tracking, etc. based on the original array data collected by the sonar. This method is actually a review of the existing array data, which can truly reflect the target detection situation in the mission sea area during the test. The disadvantage is that it is only applicable to specific scenarios and does not consider the influence brought by changes in the ocean environment. The in-machine simulator is easy to operate. After configuring parameters such as targets, hydrographic environment, and sonar array, it can realize sonar system simulation training under different ocean environments. However, the simulation effect of the simulator mainly depends on the authenticity of the constructed target radiation noise model and sound field propagation model. In some cases, the training results are relatively idealized and the restoration degree of the real scenario is not high. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies existing in the prior art, and to provide a method for outputting signals at the element level of a passive linear array sonar in a simulation system.

[0006] The purpose of the present invention is achieved by the following technical solutions. A method for outputting signals at the element level of a passive linear array sonar in a simulation system, the method includes the following steps:

[0007] Step 1: Parameter setting, including: parameters related to passive target azimuth, distance, line spectrum intensity, and platform area descent speed;

[0008] Step 2: Generate a high-sampling-rate passive target source signal, where the source signal includes the continuous spectrum of stationary continuous noise, the Demon modulation spectrum, and the Lofar discrete line spectrum;

[0009] Step 3: Calculate the time delay of the signals received by each hydrophone according to the azimuth;

[0010] Step 4: Simulate and generate the target signals received by each hydrophone;

[0011] Step 5: Simulate and generate the ocean environmental background noise received by each hydrophone;

[0012] Step 6: Superimpose the simulated signal, the simulated noise, and the actual array data to generate the full-array element data;

[0013] Step 7: Perform Fourier transform on the time-domain array element-level data and perform beamforming in the frequency domain to obtain the passive spatial energy spectrum;

[0014] Step 8: Perform long-time accumulation on the multi-beam time-domain data and obtain the multi-beam narrowband Lofar through Fourier transform.

[0015] The beneficial effects of the present invention are as follows:

[0016] Most of the existing linear array sonars carry out simulation training based on two methods: data playback and in-board simulator. The data playback processes the original array data collected from sea trials and can only complete the simulation training in specific real scenarios, where the ocean environmental factors are determined in this scenario; the in-board simulator constructs a mathematical model to simulate target radiated noise, ocean environmental noise, and ocean sound propagation, etc., and outputs the signal processing results at the array element level. However, the mathematical model often cannot accurately describe the complex ocean environment in the real world, and there are discrepancies between the simulation effect and the real situation.

[0017] The sonar simulation training method involved in the present invention combines the advantages of the above two methods. It can perform signal processing at the array element level on the real original array data, output the passive detection results of the sonar, and realize the basic function of data review. In addition, underwater acoustic targets can be added based on the original array data, and different intensities and types of ocean background noise and interference can also be added. By adjusting the energy strength of the added noise and interference, the ocean environmental noise field where the original array data is located is changed, and new array data is generated as the data sample provided to the sonar system. Based on the complex and diverse data samples, the simulation system outputs the corresponding passive signal processing results, which can simulate the difficulty of underwater acoustic target detection under the influence of background noise and interference with different intensities. The user conducts target search and tracking through the operation of the display and control terminal, and reports the tracked target information to the system assessment and management platform. The platform conducts an objective evaluation based on the assessment rules, gives a score, and feedbacks the assessment results to realize the simulation training of the underwater acoustic system. Description of the Drawings

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art or ordinary technicians, without creative efforts, other drawings can be obtained based on these drawings.

[0019] Figure 1 This is the flowchart of the passive processing algorithm of the simulation system of the present invention.

[0020] Figure 2 This is the illustration of the main interface of the training system.

[0021] Figure 3 This is the schematic diagram of setting the simulation target.

[0022] Figure 4 This is the schematic diagram of setting the target and the characteristics of ocean background noise.

[0023] Figure 5 This is the schematic diagram of selecting sample data playback.

[0024] Figure 6 This is the schematic diagram of passive warning detection.

[0025] Figure 7 This is the schematic diagram of the user reporting target information.

[0026] Figure 8 This is the schematic diagram of showing the training results. Specific implementation manners

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in combination with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0028] The present invention proposes a method for outputting element-level signals of a passive line array sonar in a simulation system, which is a new sonar simulation training method. This method combines two existing simulation training methods, combines the real original array data recorded by data playback with the simulated array data generated by the in-board simulator to generate element sample data, and performs processing processes such as filtering, sampling, and Fourier transform on the sample data, and sends the final processing result to the display and control module. Combining with the display and control interface to carry out situation judgment operations to achieve functions such as passive warning detection, target tracking, and feature analysis, and also supports users to perform custom settings for underwater acoustic targets, interferences, and ocean environmental noise fields, etc. The present invention takes into account the factors of actual ocean environment changes, can simulate the changes in the underwater acoustic target responses under different ocean environments, and is convenient for underwater acoustic technicians such as sonar soldiers to carry out teaching, training and other tasks of line array sonars.

[0029] The present invention mainly uses passive processing algorithms to process element-level signals, and methods such as filtering, beamforming, and Fourier transform are used. The algorithm processing flow is as Figure 1 shown:

[0030] The specific implementation steps of the passive processing algorithm of the simulation system are as follows:

[0031] Step 1: Parameter setting, including: passive target azimuth, distance, line spectrum intensity, platform area descent speed, etc.

[0032] Step 2: Generate a high-sampling-rate passive target source signal, and the source signal includes stationary continuous noise, Demon modulation spectrum, and Lofar discrete line spectrum, etc.

[0033] The stationary continuous noise is generated by Gaussian white noise.

[0034] y1(n) = A1gauss(n)(1.1)

[0035] A1 controls the amplitude of the stationary noise.

[0036] The modulation signal is generated by a sine signal.

[0037] y2(n) = A2sin(2πf m n / f s )(1.2)

[0038] A2 is the modulation depth, f m is the modulation frequency, f s is the signal sampling frequency.

[0039] The discrete line spectrum is also generated by a sine signal.

[0040] y3 i (n) = A 3,i sin(2πf i n / fs )(1.3)

[0041] A 3,i is the line spectrum amplitude, f i is the line spectrum frequency, i represents the generated line spectrum sequence number, and at most N line spectra are generated.

[0042] The passive target source signal can be expressed as

[0043]

[0044] Step 3: Calculate the time delay of the signals received by each hydrophone.

[0045] Assume that the passive target source signal propagates in the form of a spherical wave. Now, taking the center of the base array as the reference point, the number of array element (hydrophone) channels is M, i is the array element channel sequence number (0 ≤ i ≤ M - 1), the array element spacing is d, the distance between the target and the center of the base array is R, the incident angle of the source target signal is θ, the sound speed is c, and the time delay τ of the signals received by each array element compared to the reference point i is expressed as:

[0046]

[0047] Step 4: Simulate and generate the target signals received by each hydrophone.

[0048] y5(i,n) = y4(n - fs * τ i )(1.6)

[0049]

[0050] y7(i,m) = y6(i,k * n)(1.8)

[0051] i is the hydrophone channel number, n and m represent the discrete points of the time-domain signals received by the hydrophone before and after downsampling. h1(n) is the designed signal filter, which realizes functions such as signal octave attenuation and low-pass filtering. y7 is the simulated time-domain signal received by the hydrophone after downsampling.

[0052] Step 5: Simulate and generate the ocean environmental background noise received by each hydrophone.

[0053] y8(i,n) = A6gauss(i,n)(1.9)

[0054]

[0055] y10(i,m) = y9(i,k * n)(1.11)

[0056] A6 controls the amplitude of the ocean environmental noise, and y10 is the simulated ocean background noise received by each hydrophone after downsampling.

[0057] Step 6: Generate the full-array element data by superimposing the analog signal, analog noise, and actual array data.

[0058] y12(i,m) = y7(i,m) + y10(i,m) + y11(i,m) (1.12)

[0059] y11 is the actual array data, and y12 is the element-level data that includes the analog signal, noise, and actual array data.

[0060] Step 7: Perform Fourier transform on the time-domain element-level data and frequency-domain beamforming to obtain the passive spatial energy spectrum.

[0061] y13(i,f) = fft(y12(i,m)) (1.13)

[0062] a(θ,i) = exp(-j*2*pi*f*τ i ) (1.14)

[0063] y14(θ,f) = a(θ,i) H *y13(i,f) (1.15)

[0064]

[0065] f represents the frequency point of the element data after Fourier transform, θ is the preformed beam angle, y13 is the frequency-domain array data, a is the scanning steering vector. Perform beamforming on y13 to obtain the multi-beam frequency-domain data y14, and then perform frequency point energy accumulation to obtain the spatial energy spectrum y15. In Equation (1.16), f_low and f_high are the upper and lower limits of the frequencies for frequency point energy accumulation.

[0066] Step 8: Perform long-time accumulation on the multi-beam time-domain data and obtain the multi-beam narrowband Lofar through Fourier transform.

[0067] y16(θ,m) = ifft(y14(θ,f))(1.17)

[0068] After performing the inverse Fourier transform on the multi-beam frequency-domain data y14, obtain the multi-beam time-domain data y16. Accumulate it with the previously processed time-domain data to form a long-time data vector y17, and perform FFT processing on it to obtain the multi-beam narrowband Lofar.

[0069] y18(θ,f) = fft(y17(θ,m))(1.18).

[0070] The operation method of this simulation system is generally divided into the following steps, as Figures 2 - 8 shown:

[0071] Step 1: Set sample data parameters. Select the original array data to be replayed on the display and control interface, set the appearance and disappearance times of passive simulated targets and interferences, as well as attribute features such as speed, course, line spectrum frequency, line spectrum intensity, etc.; adjust the setting of the ocean environmental background noise level to change the ocean environmental noise field where the original array data is located.

[0072] Step 2: Generate replayed sample data. Start the original element database to start the replay of element data, produce sample data in the element domain, and store the recorded sample data in the sample database after the recording is completed.

[0073] Step 3: The user replays the sample data, starts the sample database to start the signal processing process, sets signal processing parameters, and conducts operations such as target tracking and feature analysis on the warning detection screen.

[0074] Step 4: Upload the tracking operation information to the system assessment and management platform, and the platform gives an objective evaluation score based on the assessment rules.

[0075] The present invention combines the simulated data of the linear array in the ideal scenario with the measured array data, has a replay function, and supports the review of the original array data. On this basis, underwater acoustic targets, noises, and interferences are added to output array sample data, supporting trainees to carry out training and assessment such as passive warning detection and target tracking.

[0076] The element-level signal simulation method constructed by the present invention can superimpose targets, white noises, and interferences on the basis of the original array data according to the target motion parameters and ocean environmental parameters issued by the display and control, generate element data samples for spectrogram training, and replay the data samples to achieve passive detection. This method combines the theoretical array data obtained by traditional in-aircraft simulator simulation with the measured array data to obtain the signal processing output results under the conditions of ocean environmental changes and target changes, facilitating the carrying out of tasks such as linear array sonar simulation training teaching and training.

[0077] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claimed rights.

Claims

1. A method for signal output at the element level of a passive linear array sonar in a simulation system, characterized in that: The method includes the following steps: Step 1: Parameter setting, including: parameters related to the azimuth, distance, line spectrum intensity, and platform area descent speed of the passive target; Step 2: Generate a high-sampling-rate passive target source signal, where the source signal includes the continuous spectrum of stationary continuous noise, the Demon modulation spectrum, and the Lofar discrete line spectrum; Step 3: Calculate the time delay of the received signal of each hydrophone according to the azimuth; Step 4: Simulate and generate the target signals received by each hydrophone; Step 5: Simulate and generate the ocean environmental background noise received by each hydrophone; Step 6: Superimpose the simulated signal, simulated noise, and actual array data to generate the full-array element data; Step 7: Perform a Fourier transform on the time-domain array element data, and perform beamforming in the frequency domain to obtain the passive spatial energy spectrum; Step 8: Perform long-time accumulation on the multi-beam time-domain data, and obtain the multi-beam narrowband Lofar through Fourier transform.

2. The method for outputting signals at the element level of a passive line array sonar in the simulation system according to claim 1, characterized in that: In Step 2, to generate a high-sampling-rate passive target source signal, the specific steps are as follows: The stationary continuous noise is generated by Gaussian white noise: y1(n) = A1gauss(n)(1.1) A1 controls the amplitude of the stationary noise; The modulation signal is generated by a sine signal: y2(n) = A2sin(2πf m n / f s )(1.2) A2 is the modulation depth, and f m is the modulation frequency, and f s is the signal sampling frequency; The discrete line spectrum is also generated by a sine signal: y3 i (n) = A 3,i sin(2πf i n / f s )(1.3) A 3,i is the line spectrum amplitude, f i is the line spectrum frequency, i represents the generated line spectrum serial number, and at most N line spectra are generated; The passive target source signal is expressed as:

3. The method for outputting signals at the element level of a passive line array sonar in the simulation system according to claim 2, wherein: In the third step, assuming that the passive target source signal propagates in the form of a spherical wave, taking the center of the base array as the reference point, the number of array element channels is M, i is the array element channel serial number, 0 ≤ i ≤ M - 1, the array element spacing is d, the distance between the target and the center of the base array is R, the incident angle of the source target signal is θ, the speed of sound is c, and the time delay τ of the received signal of each array element compared with the reference point i It is expressed as:

4. The method for outputting signals at the element level of a passive line array sonar in the simulation system according to claim 3, wherein: In Step 4, to simulate and generate the target signals received by each hydrophone, the specific steps are as follows: y5(i,n) = y4(n - fs*τ i )(1.6) y7(i,m) = y6(i,k*n)(1.8) Where, i is the hydrophone channel number, n and m represent the discrete points of the time-domain signal received by the hydrophone before and after downsampling, h1(n) is the designed signal filter to achieve functions related to signal octave attenuation and low-pass filtering, and y7 is the simulated time-domain signal received by the hydrophone after downsampling.

5. The method for outputting signals at the element level of a passive line array sonar in the simulation system according to claim 4, wherein: In Step 5, to simulate and generate the ocean environmental background noise received by each hydrophone, the specific steps are as follows: y8(i,n) = A6gauss(i,n)(1.9) y10(i,m) = y9(i,k*n)(1.11) A6 controls the amplitude of the ocean environmental noise, and y10 is the simulated ocean background noise received by each hydrophone after downsampling.

6. The method for outputting signals at the element level of a passive line array sonar in the simulation system according to claim 5, characterized in that: In Step 6, to superimpose the simulated signal, simulated noise, and actual array data to generate the full-array element data, the specific steps are as follows: y12(i,m) = y7(i,m) + y10(i,m) + y11(i,m)(1.12) y11 is the actual array data, and y12 is the array element-level data containing the simulated signal, noise, and actual array data.

7. The method for outputting signals at the element level of a passive line array sonar in the simulation system according to claim 6, characterized in that: In Step 7, to perform a Fourier transform on the time-domain array element data, and perform beamforming in the frequency domain to obtain the passive spatial energy spectrum, the specific steps are as follows: y13(i,f) = fft(y12(i,m))(1.13) a(θ,i) = exp(-j * 2 * pi * f * τ i )(1.14) y14(θ,f) = a(θ,i) H *y13(i,f)(1.15) Where, f represents the frequency point of the array element data after Fourier transform, θ is the preformed beam angle, y13 is the frequency-domain array data, a is the scanning steering vector, perform beamforming on y13 to obtain the multi-beam frequency-domain data y14, and then perform frequency point energy accumulation to obtain the spatial energy spectrum y15, f_low and f_high are the upper and lower limits of the frequency for frequency point energy accumulation.

8. The method for outputting signals at the element level of a passive linear array sonar in the simulation system according to claim 7, wherein: In the eighth step, the multi-beam time-domain data is cumulated for a long time and the multi-beam narrowband Lofar is obtained through Fourier transform. The specific steps are as follows: y16(θ,m) = ifft(y14(θ,f))(1.17) The multi-beam time-domain data y16 is obtained after performing the inverse Fourier transform on the multi-beam frequency-domain data y14. It is cumulated with the previously processed time-domain data to form a long-time data vector y17, and then FFT processing is performed on it to obtain the multi-beam narrowband Lofar; y18(θ,f) = fft(y17(θ,m))(1.18).

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