Volumetric array beam control method based on particle swarm optimization in deep sea environment

Abstract

The invention provides a particle swarm optimization-based volume array beam control method in a deep sea environment, which comprises the following steps of: sectionally using a volume array, simultaneously performing beam control in a horizontal direction and a seabed direction, and distinguishing echo signal frequency spectrums in a mode of transmitting orthogonal signals, so that continuous detection of targets in a convergence area and an acoustic shadow area by the volume array is realized. Meanwhile, angle optimization is carried out by utilizing the particle swarm optimization, the optimal beam control angle is obtained when beam control towards the seabed is carried out, namely, the hidden region target is detected by utilizing a seabed bounce mode, the problem that the beam control angle is difficult to determine in the prior art is solved, and the method has certain practicability. For detection efficiency evaluation, a high-quality factor (FOM) is used for quantitative analysis, and the purpose of obtaining the optimal seabed beam control angle under the condition of traversing all possible beam control directions is achieved in combination with efficiency evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of beam control methods, and mainly relates to a volume array beam control method based on a particle swarm algorithm in a deep-sea environment. Background Art

[0002] In the deep-sea waveguide environment, the water temperature, salinity, pressure and other parameter gradients vary greatly, forming a complex acoustic tomography structure, which makes the sound propagation path tortuous and changeable. At the same time, interference factors such as the undulating seabed topography and sea surface wind waves further increase the uncertainty of sound propagation, bringing certain challenges to underwater detection tasks. The beam control technology is an indispensable key technology for sonar equipment to improve detection performance. By optimizing the formation and direction of sound waves, this technology can form sound intensity aggregation in a specific area. However, the traditional beam control method can only observe the space covered by one beam angle in one transmission and reception, with certain detection limitations.

[0003] The traditional beam control method takes a single beam control angle as the input, and can only observe the space covered by one beam angle in one transmission and reception, and cannot achieve continuous detection of targets in different areas such as convergence areas and shadow areas.

[0004] The currently most similar technical solution to the present invention is to obtain the beam control angle by using angular spectrum domain analysis. This method obtains the angular spectrum domain distribution of the sound field by calculating the relationship between the outgoing angles and relative intensities of each order of normal modes, and guides the selection of the beam control angle. The angular spectrum domain method can provide certain support for the selection of the beam control angle, but limited by the cut-off frequency of the normal mode, the angular spectrum domain method covers a limited angle. Summary of the Invention

[0005] Aiming at the problem that it is difficult for sonar systems in deep-sea waveguides to achieve continuous detection of targets, the present invention provides a volume array beam control method based on a particle swarm algorithm in a deep-sea environment.

[0006] The object of the present invention is achieved by the following technical solutions. A volume array beam control method based on a particle swarm algorithm in a deep-sea environment includes the following steps: preset the performance prediction calculation parameters of sonar equipment, use the volume array in segments, beam control in both the horizontal direction and the seabed direction at the same time, and distinguish the echo signals in the frequency spectrum by transmitting orthogonal signals, so as to achieve continuous detection of targets in the convergence area and the acoustic shadow area by the volume array.

[0007] Further, the specific steps of presetting the performance prediction calculation parameters of sonar equipment are as follows: According to the active sonar equation, the figure of merit FOM is expressed as:

[0008] FOM = SL - NL + DI - DT + TS

[0009] Wherein, SL is the transmitting source level, NL is the ambient noise level, DI is the receiving directivity index, DT is the detection threshold, and TS is the target strength.

[0010] Furthermore, the volume array is used in segments and beam-controlled in the horizontal direction, including the following steps:

[0011] (1) Divide the volume array into two segments, L 1 and L 2 , and select orthogonal frequencies f 1 and f 2 , where f 1 is used as the transmission frequency for beam-control of the volume array L 1 in the horizontal direction, and f 2 is used as the transmission frequency for beam-control of the volume array L 2 in the direction towards the seabed;

[0012] (2) Coherently superpose the sound fields of each element of the volume array L 1 and calculate the propagation loss after horizontal beam control;

[0013] (3) At the target depth, compare the two-way propagation loss of the volume array L 1 after horizontal beam control with the FOM to evaluate the effective detection range.

[0014] Furthermore, beam-control in the direction towards the seabed includes the following steps:

[0015] (1) Use the particle swarm optimization algorithm for optimization. Through iterative calculation, obtain the optimal beam-control angle when the volume array is beam-controlled towards the seabed;

[0016] (2) According to the optimal beam-control angle, perform time delay and coherent superposition of the sound fields of each element of the volume array L 2 and calculate the propagation loss after beam-control towards the seabed;

[0017] (3) At the target depth, compare the two-way propagation loss of the volume array L 2 after beam-control towards the seabed with the FOM to evaluate the effective detection range.

[0018] Furthermore, using the particle swarm optimization algorithm to optimize the beam-control angle towards the seabed includes the following steps:

[0019] (1) Assume that the range of the beam-control angle towards the seabed is from -90° to 90°;

[0020] (2) Set the particle swarm optimization parameters, including: the number of individuals in the population N, the maximum number of iterations T, the inertia weight w, the acceleration constants c 1 and c 2 and the maximum velocity v max of the particles;

[0021] (3) Initialize the particle swarm, set the historical optimal value p best to 0, and randomly set the position x iand velocity v i whose position is x i representing angles, the parameters should satisfy the following conditions:

[0022]

[0023] 0 ≤ v i ≤ v max

[0024] (4) According to the parameters of each particle and the calculation results of Kraken, conduct detection efficiency prediction to obtain the volume array L 2 The detection ranges under different beam control angles are used as the fitness values fit(i) of the particles;

[0025] (5) For each particle, compare its fitness value fit(i) with the historical optimal value p best If fit(i) > p best , then replace p with fit(i) best ;

[0026] (6) Update the particle velocity v i and position x i , and determine whether the iteration stop condition is satisfied. If it is satisfied, output the optimal beam control angle; otherwise, return to step (4).

[0027] The beneficial effects of the present invention are as follows: To achieve continuous detection of targets in different regions such as the deep - sea convergence zone and acoustic shadow zone by the volume array, the present invention proposes a method of using the volume array in segments, transmitting orthogonal signals, and performing beam control in both the horizontal direction and the seabed direction.

[0028] 1. The present invention uses the volume array in segments, performs beam control in different directions, and realizes the distinction of echo signal spectra by transmitting orthogonal signals, achieving the purpose of continuous detection in multiple regions.

[0029] 2. The present invention uses the particle swarm algorithm for angle optimization, takes - 90° to 90° as the algorithm input, and obtains the optimal beam control angle for detecting targets in the shadow zone by using the seabed bounce mode through iterative calculation, solving the problem that it is difficult to determine the beam control angle in the prior art, and having a certain practicality.

[0030] 3. For the detection efficiency evaluation, the present invention uses the figure of merit (FOM) for quantitative analysis, and combines the efficiency evaluation to obtain the optimal seabed beam control angle under the condition of traversing all possible beam control directions. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required in the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those skilled in the art or ordinary technicians, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0032] Figure 1 It is a schematic diagram of the working process of the present invention.

[0033] Figure 2 It is a schematic diagram of a typical deep - sea sound speed profile.

[0034] Figure 3 It is the volume array L 1 It is a schematic diagram of the propagation loss after horizontal beamforming control.

[0035] Figure 4 It is the volume array L 1 It is a schematic diagram comparing the two - way propagation loss and FOM after horizontal beamforming control.

[0036] Figure 5 It is the volume array L 2 It is a schematic diagram of the propagation loss after seabed beamforming control.

[0037] Figure 6 It is the volume array L 2 It is a schematic diagram comparing the two - way propagation loss and FOM after beamforming control towards the seabed.

[0038] Figure 7 It is the volume array L 1 and L 2 It is a schematic diagram of the propagation loss when working simultaneously.

[0039] Figure 8 It is the volume array L 1 and L 2 It is a schematic diagram comparing the two - way propagation loss and FOM at the target depth when working simultaneously. Specific embodiments

[0040] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying 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.

[0041] The present invention discloses a volume array beamforming control method based on the particle swarm algorithm in a deep - sea environment, and its working process is as Figure 1As shown in the figure, the steps are as follows: preset the calculation parameters for sonar equipment performance prediction, use the volume array in segments, beam control in both the horizontal direction and the seabed direction, and distinguish the echo signals in the frequency spectrum by transmitting orthogonal signals, so as to realize the continuous detection of targets in the convergence zone and the acoustic shadow zone by the volume array.

[0042] 1. Preset the sonar equipment performance prediction parameters. According to the active sonar equation, the figure of merit FOM can be expressed as:

[0043] FOM = SL - NL + DI - DT + TS

[0044] where SL is the transmitting source level, NL is the ambient noise level, DI is the receiving directivity index, DT is the detection threshold, and TS is the target strength.

[0045] Figure 2 is a typical sound speed profile in the deep sea, showing a negative gradient characteristic on the surface, forming a sound channel axis at a depth of about 1300m, showing a positive gradient characteristic below the sound channel axis, and the seabed is a homogeneous medium half-space.

[0046] 2. Use the volume array in segments and beam control in the horizontal direction, including the following steps:

[0047] (1). Divide the volume array into L 1 and L 2 two segments, select orthogonal frequencies f 1 and f 2 , where f 1 is used as the transmitting frequency for beam control of the volume array L 1 in the horizontal direction, and f 2 is used as the transmitting frequency for beam control of the volume array L 2 in the seabed direction;

[0048] (2). Coherently superpose the sound fields of each element of the volume array L 1 and calculate the propagation loss after horizontal beam control; as Figure 3 shown, the propagation loss of the volume array L 1 after horizontal beam control has significant deep-sea convergence zone characteristics.

[0049] (3). Compare the two-way propagation loss of the volume array L 1 after horizontal beam control with the FOM at the target depth to evaluate the effective detection range. From the results shown in Figure 4 , it can be obtained that the detection distance of the volume array L 1 after horizontal beam control can cover the convergence zones centered at 64km, 128km, 192km, and 256km.

[0050] 3. Beam control in the seabed direction, including the following steps:

[0051] Optimize using the particle swarm algorithm. Through iterative calculations, obtain the optimal beam control angle when the volume array is beam controlled towards the seabed;

[0052] (1) Assume that the range of the seabed beam control angle is from -90° to 90°;

[0053] (2) Set the particle swarm optimization parameters, mainly including: the number of individuals in the population N, the maximum number of iterations T, the inertia weight w, the acceleration constants c 1 、c 2 and the maximum particle velocity v max etc.;

[0054] (3) Initialize the particle swarm, set the historical optimal value p best to 0, and randomly set the position x i and velocity v i of each particle. Its position x i represents the angle, and each parameter should satisfy the following conditions:

[0055]

[0056] 0 ≤ v i ≤ v max

[0057] (4) According to the parameters of each particle and the Kraken calculation results, conduct detection efficiency prediction to obtain the detection range of the volume array L 2 at different beam control angles, which is used as the fitness value fit(i) of the particle;

[0058] (5) For each particle, compare its fitness value fit(i) with the historical optimal value p best . If fit(i) > p best , then replace p best with fit(i);

[0059] (6) Update the particle velocity v i and position x i , and determine whether the iteration stop condition is satisfied. If it is satisfied, output the optimal beam control angle; otherwise, return to step (4).

[0060] According to the optimal beam control angle output by the particle swarm algorithm, delay and coherently superimpose the sound fields of each element of the volume array L 2 to calculate the propagation loss after beam control towards the seabed. As Figure 5 shown, after beam control towards the seabed, obvious sound intensity aggregation has formed in the sound shadow area within the first convergence zone of the volume array L 2 .

[0061] At the target depth, the volume array L 2Compare the two-way propagation loss after beam steering to the seabed with the FOM to evaluate the effective detection range. From Figure 6 The results shown, after implementing beam steering to the seabed, the volume array L 2 has the ability to detect and cover the area from 11 km to 45 km outside the original detection range.

[0062] Volume array L 1 and L 2 When working simultaneously, according to the principle of coherent superposition of the sound field, the propagation loss is as Figure 7 shown, and the comparison result of the two-way propagation loss at the target depth with the FOM is as Figure 8 shown. From the results shown in the figure, by using the volume array in segments, transmitting orthogonal signals, and beam steering in both the horizontal direction and the seabed direction simultaneously, continuous detection of targets in the convergence zone and shadow zone can be achieved.

[0063] As described above, it 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 claims described.

Claims

1. A volume array beam control method based on particle swarm algorithm in deep sea environment, characterized by: The method includes the following steps: presetting the sonar equipment performance prediction calculation parameters, using the volume array in segments, controlling the beam in the horizontal direction and the seabed direction at the same time, and distinguishing the echo signal spectrum by emitting orthogonal signals, thereby realizing continuous detection of targets in the convergence area and the acoustic shadow area by the volume array.

2. The volume array beam control method based on particle swarm algorithm in deep sea environment according to claim 1, characterized in that: The preset sonar equipment performance prediction calculation parameters include the following specific steps: According to the active sonar equation, the quality factor FOM is expressed as: FOM=SL-NL+DI-DT+TS Among them, SL is the transmitting sound source level, NL is the ambient noise level, DI is the receiving directivity index, DT is the detection threshold, and TS is the target strength.

3. The volume array beam control method based on particle swarm algorithm in deep sea environment according to claim 2, characterized in that: The volume array is divided into segments and beam controlled in the horizontal direction, including the following steps: (1) Divide the volume array into two segments, L1 and L2, and select orthogonal frequencies f1 and f2, where f1 is used as the transmission frequency of the volume array L1 for beam control in the horizontal direction, and f2 is used as the transmission frequency of the volume array L2 for beam control in the seabed direction; (2) Coherently superimpose the sound fields of each element of volume array L1 and calculate the propagation loss after horizontal beam control; (3) At the target depth, the two-way propagation loss after horizontal beam control of the volume array L1 is compared with the FOM to evaluate the effective detection range.

4. The volume array beam control method based on particle swarm algorithm in deep sea environment according to claim 3, characterized in that: Beam control towards the seabed includes the following steps: (1) Using the particle swarm algorithm to find the optimal beam control angle of the volume array toward the seabed through iterative calculation; (2) According to the optimal beam steering angle, the acoustic field of each element of volume array L2 is delayed and coherently superimposed to calculate the propagation loss after beam steering to the seabed; (3) At the target depth, the two-way propagation loss of the volume array L2 after beam steering to the seabed is compared with the FOM to evaluate the effective detection range.

5. The volume array beam control method based on particle swarm algorithm in deep sea environment according to claim 4, characterized in that: The particle swarm algorithm is used to optimize the seabed beam control angle, including the following steps: (1) Assume that the seabed beam control angle range is -90° to 90°; (2) Set the particle swarm optimization parameters, including: the number of individuals N, the maximum number of iterations T, the inertia weight w, the acceleration constants c1, c2 and the maximum particle speed v max ; (3) Initialize the particle swarm and set the historical optimal value p best Set to 0, randomly set the position x of each particle i and speed v i , whose position x i Represents the angle, and each parameter should meet the following conditions: 0≤v i ≤v max (4) According to the particle parameters and Kraken calculation results, the detection performance is predicted, and the detection range of the volume array L2 at different beam control angles is obtained as the particle fitness value fit(i); (5) For each particle, use its fitness value fit(i) and historical optimal value p best Compare, if fit(i)>p best , then replace p with fit(i) best ; (6) Update particle velocity v i and position x i , and determine whether the iteration stop condition is met. If so, the optimal beam control angle is output, otherwise, return to step (4).

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