An new LFM detection algorithm based on ADTR-FrFT for active sonar system

2017 ◽  
Author(s):  
Zhichen Zhang ◽  
Haiyan Wang ◽  
Zhengguo Liu ◽  
Xiaohong Shen ◽  
Zhe Jiang ◽  
...  
Keyword(s):  
Detection Algorithm ◽  
Active Sonar ◽  
Sonar System

scholarly journals Underwater Moving Target Classification Using Multilayer Processing of Active Sonar System

2019 ◽  
Vol 9 (21) ◽  
pp. 4617
Author(s):  
Iksu Seo ◽  
Seongweon Kim ◽  
Youngwoo Ryu ◽  
Jungyong Park ◽  
Dong Seog Han
Keyword(s):  
Ambient Noise ◽  
Roc Curves ◽  
Detection Algorithm ◽  
Classification Performance ◽  
Probability Of Detection ◽  
Support Vector ◽  
High Signal ◽  
Classification Rate ◽  
Active Sonar ◽  
Sonar System

The task of detecting and classifying highly maneuverable and unidentified underwater targets in complex environments is significant in active sonar systems. Previous studies have applied many detection schemes to this task using signals above a preset threshold to separate targets from clutter; this is because a high signal-to-noise ratio (SNR) target has sufficient feature vector components to be separated out. However, in real environments, the received target return’s SNR is not always above the threshold. Therefore, a target detection algorithm is needed for varied target SNR conditions. When the clutter energy is too strong, false detection can occur, and the probability of detection is reduced due to the weak target signature. Furthermore, since a long pulse repetition interval is used for long-range detection and ambient noise tends to be high, classification processing for each ping is needed. This paper proposes a multilayer classification algorithm applicable to all signals in real underwater environments above the noise level without thresholding and verifies the algorithm’s classification performance. We obtained a variety of experimental data by using a real underwater target and a hull-mounted active sonar system operated on Korean naval ships in the East Sea, Korea. The detection performance of the proposed algorithm was evaluated in terms of the classification rate and false alarm rate as a function of the SNR. Since experimental environment data, including the sea state, target maneuvering patterns, and sound speed, were available, we selected 1123 instances of ping data from the target over all experiments and randomly selected 1000 clutters based on the distribution of clutters for each ping. A support vector machine was employed as the classifier, and 80% of the data were selected for training, leaving the remaining data for testing. This process was carried out 1000 times. For the performance analysis and discussions, samples of scatter diagrams and feature characteristics are shown and classification tables and receiver operation characteristic (ROC) curves are presented. The results show that the proposed algorithm is effective under a variety of target strengths and ambient noise levels.

scholarly journals Doppler Data Association Scheme for Multi-Target Tracking in an Active Sonar System

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2003
Author(s):  
Yu Yao ◽  
Junhui Zhao ◽  
Lenan Wu
Keyword(s):  
Target Tracking ◽  
Data Association ◽  
Target Range ◽  
Target Velocity ◽  
Linear Filter ◽  
Velocity Measurements ◽  
Active Sonar ◽  
Sonar System ◽  
Multi Target Tracking ◽  
Doppler Data

In many wireless sensors, the target kinematic states include location and Doppler information that can be observed from a time series of range and velocity measurements. In this work, we present a tracking strategy for comprising target velocity components as part of the measurement supplement procedure and evaluate the advantages of the proposed scheme. Data association capability can be considered as the key performance for multi-target tracking in an active sonar system. Then, we proposed an enhanced Doppler data association (DDA) scheme which exploits target range and target velocity components for linear multi-target tracking. If the target velocity measurements are not incorporated into target kinematic state tracking, the linear filter bank for the combination of target velocity components can be implemented. Finally, a significant enhancement in the multi-target tracking capability provided by the proposed DDA scheme with the linear multi-target combined probabilistic data association method is demonstrated in a sonar underwater scenario.

Visualizing Probability of Detection to Aid Sonar Operator Performance

2017 ◽  
Vol 61 (1) ◽  
pp. 302-306 ◽  
Author(s):  
Kingsley I. Fletcher ◽  
Megan L. Bartlett ◽  
Susan J. Cockshell ◽  
Jason S. McCarley
Keyword(s):  
Spatial Attention ◽  
Target Detection ◽  
Response Bias ◽  
Human Performance ◽  
Detection Task ◽  
Probability Of Detection ◽  
Uncertainty Range ◽  
Active Sonar ◽  
Operator Performance ◽  
Sonar System

This study tested whether the display of rings indicating the probability of target detection would improve human performance on a simulated active sonar detection task. Participants viewed a series of simulated sonar returns and decided whether a target was present or not. Participants performed the task both with and without uncertainty range rings that indicated 90% and 10% detectability ranges. The probability of detection rings did not improve the overall ability of participants to distinguish targets from noise, but did appear to influence response bias and spatial attention. These results suggest that displaying probability of detection may not be an effective way of improving the performance of sonar system operators.

An active sonar system using ACVD beamforming

1989 ◽  
Vol 27 (4) ◽  
pp. 275-285 ◽  
Author(s):  
Ian G. Bryden
Keyword(s):  
Active Sonar ◽  
Sonar System

Recent Developments in Numerical Modeling of Transduction Materials

1995 ◽  
Author(s):  
Anne-Christine Hladky-Hennion ◽  
Régis Bossut ◽  
Jean-Claude Debus
Keyword(s):  
Finite Element ◽  
Numerical Modeling ◽  
Research Work ◽  
Piezoelectric Composite ◽  
The Finite Element Method ◽  
Theoretical Formulation ◽  
Active Sonar ◽  
Sonar System ◽  
Recent Developments ◽  
Materials Used

Abstract Recent research work in sonar system performance, coupled with achievements in the field of acoustic quieting, has led to the development of new ceramics that are promising for both hydrophone and projector applications. Other materials have also been studied like piezoelectric composite materials, magnetostrictive and electrostrictive materials. To design transducers using these materials, the finite element method seems to be the best suited approach. Using this method, it is possible to analyze, characterize and tailor new materials as well as to design a full transducer or an array. Recent developments in the ATILA finite element code allow the modeling of new transduction materials. The aim of this paper is to present the theoretical formulation in numerical modeling of materials used either for hydrophone or active sonar applications.

Research on BatSLAM Algorithm for UAV Based on Audio Perceptual Hash Closed-Loop Detection

2018 ◽  
Vol 33 (01) ◽  
pp. 1959002 ◽  
Author(s):  
Mengyuan Chen ◽  
Wenchao Hu
Keyword(s):  
Closed Loop ◽  
Simulation Experiment ◽  
Energy Difference ◽  
Detection Algorithm ◽  
Absolute Difference ◽  
Sonar System ◽  
Loop Detection ◽  
Perceptual Hash ◽  
Geometric Processing ◽  
Dark Conditions

This research is aimed at the optimization of a two-dimensional (2D) empirical graph under a certain height and dark conditions for a UAV, using the bionic sonar system to replace the visual sensor’s BatSLAM mode and audio perceptual hash closed-loop detection. The BatSLAM model uses Sum of Absolute Difference (SAD) image processing methods to update the bionic sonar template. This method only judges whether the appearance of the two cochlear images is consistent and does not have geometric processing and feature extraction. Because the cochlear images produce various noises during the acquisition and transmission, there are some differences in cochlear maps obtained at the same position, which can lead to the distortion of the constructed empirical map. In this research, an audio perceptual hash closed-loop detection algorithm is developed to extract features of cochlea. It considers both the appearance and the energy difference between adjacent bands to improve the accuracy of closed-loop detection, thus solving the distortion problem and improving the experience map. The simulation experiment shows that the improved BatSLAM model based on the audio perceptual hash closed-loop detection can improve the 2D experience map for UAV under certain height and dark conditions, through improving the accuracy of the closed-loop detection to solve the distortion problem and thus implementing the optimization of the experience graph.

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