scholarly journals Batch Processing through Particle Swarm Optimization for Target Motion Analysis with Bottom Bounce Underwater Acoustic Signals

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1234
Author(s):  
Raegeun Oh ◽  
Taek Lyul Song ◽  
Jee Woong Choi
Keyword(s):  
Particle Swarm Optimization ◽  
Motion Analysis ◽  
Acoustic Signals ◽  
Batch Processing ◽  
Target Motion ◽  
Horizontal Line ◽  
Swarm Optimization ◽  
Conical Angle ◽  
Line Array ◽  
Target Motion Analysis

A target angular information in 3-dimensional space consists of an elevation angle and azimuth angle. Acoustic signals propagating along multiple paths in underwater environments usually have different elevation angles. Target motion analysis (TMA) uses the underwater acoustic signals received by a passive horizontal line array to track an underwater target. The target angle measured by the horizontal line array is, in fact, a conical angle that indicates the direction of the signal arriving at the line array sonar system. Accordingly, bottom bounce paths produce inaccurate target locations if they are interpreted as azimuth angles in the horizontal plane, as is commonly assumed in existing TMA technologies. Therefore, it is necessary to consider the effect of the conical angle on bearings-only TMA (BO-TMA). In this paper, a target conical angle causing angular ambiguity will be simulated using a ray tracing method in an underwater environment. A BO-TMA method using particle swarm optimization (PSO) is proposed for batch processing to solve the angular ambiguity problem.

scholarly journals A Hybrid Newton–Raphson and Particle Swarm Optimization Method for Target Motion Analysis by Batch Processing

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2033
Author(s):  
Raegeun Oh ◽  
Yifang Shi ◽  
Jee Woong Choi
Keyword(s):  
Particle Swarm Optimization ◽  
Motion Analysis ◽  
Hybrid Method ◽  
Heuristic Algorithms ◽  
Particle Swarm ◽  
Optimization Method ◽  
Batch Processing ◽  
Swarm Optimization ◽  
Newton Raphson ◽  
Target Motion Analysis

Bearing-only target motion analysis (BO-TMA) by batch processing remains a challenge due to the lack of information on underwater target maneuvering and the nonlinearity of sensor measurements. Traditional batch estimation for BO-TMA is mainly performed based on deterministic algorithms, and studies performed with heuristic algorithms have recently been reported. However, since the two algorithms have their own advantages and disadvantages, interest in a hybrid method that complements the disadvantages and combines the advantages of the two algorithms is increasing. In this study, we proposed Newton–Raphson particle swarm optimization (NRPSO): a hybrid method that combines the Newton–Raphson method and the particle swarm optimization method, which are representative methods that utilize deterministic and heuristic algorithms, respectively. The BO-TMA performance obtained using the proposed NRPSO was tested by varying the measurement noise and number of measurements for three targets with different maneuvers. The results showed that the advantages of both methods were well combined, which improved the performance.

scholarly journals Robust target motion analysis using the possibility particle filter

2019 ◽  
Vol 13 (1) ◽  
pp. 18-22 ◽  
Author(s):  
Branko Ristic ◽  
Jeremie Houssineau ◽  
Sanjeev Arulampalam
Keyword(s):  
Particle Filter ◽  
Motion Analysis ◽  
Target Motion ◽  
Target Motion Analysis

scholarly journals Simultaneous Design of Low-Pass Filter with Impedance Matching Transformer for SONAR Transducer Using Particle Swarm Optimization

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4646
Author(s):  
Jae-Hyuk Choi ◽  
Hyung-Soo Mok
Keyword(s):  
Particle Swarm Optimization ◽  
Impedance Matching ◽  
Particle Swarm ◽  
Acoustic Signals ◽  
Design Methods ◽  
Swarm Optimization ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Simultaneous Design ◽  
Low Pass

Sound navigation and ranging (SONAR) systems detect a target in the front direction by using acoustic signals. A switching-type power conversion system is used to improve power efficiency, and an impedance matching circuit is used to decrease reactive power. A low-pass filter is used to improve the quality of acoustic signals. To achieve the desired voltage level for a SONAR transducer, a transformer is connected in series with a low-pass filter. In conventional design methods, design value errors occur because the components are designed independently and later combined. Moreover, if parameters that considerably impact operating characteristics are ignored in the design process, these errors will increase. Hence, time and cost losses are incurred during refabrication because operational characteristics differ from design values. To solve this problem, this study proposes the simultaneous design of a low-pass filter and impedance matching circuit, which includes critical design parameters, utilizing the particle swarm optimization algorithm. Moreover, conventional design methods were examined, and the superiority of the proposed design method to conventional methods was verified through analyses and experiments in terms of overall impedance phase and filter blocking characteristics.

Bearings‐only target motion analysis of a highly manoeuvring target

2017 ◽  
Vol 11 (6) ◽  
pp. 1011-1019 ◽  
Author(s):  
Jonghoek Kim ◽  
Taeil Suh ◽  
Jonha Ryu
Keyword(s):  
Motion Analysis ◽  
Target Motion ◽  
Target Motion Analysis
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