Source localization performance of a multi-array network under sensor orientation and position uncertainty

2008 ◽  
Author(s):  
Brent Gold ◽  
Michael J. Roan ◽  
Marty Johnson ◽  
Elizabeth Hoppe
Keyword(s):  
Source Localization ◽  
Position Uncertainty ◽  
Sensor Orientation ◽  
Localization Performance

scholarly journals A Novel Method for Asynchronous Time-of-Arrival-Based Source Localization: Algorithms, Performance and Complexity

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3466
Author(s):  
Yuanpeng Chen ◽  
Zhiqiang Yao ◽  
Zheng Peng
Keyword(s):  
Source Localization ◽  
Signal Propagation ◽  
Least Square ◽  
Time Of Arrival ◽  
Propagation Time ◽  
Performance Loss ◽  
Localization Algorithms ◽  
Least Square Problem ◽  
Localization Performance ◽  
Asynchronous State

In time-of-arrival (TOA)-based source localization, accurate positioning can be achieved only when the correct signal propagation time between the source and the sensors is obtained. In practice, a clock error usually exists between the nodes causing the source and sensors to often be in an asynchronous state. This leads to the asynchronous source localization problem which is then formulated to a least square problem with nonconvex and nonsmooth objective function. The state-of-the-art algorithms need to relax the original problem to convex programming, such as semidefinite programming (SDP), which results in performance loss. In this paper, unlike the existing approaches, we propose a proximal alternating minimization positioning (PAMP) method, which minimizes the original function without relaxation. Utilizing the biconvex property of original asynchronous problem, the method divides it into two subproblems: the clock offset subproblem and the synchronous source localization subproblem. For the former we derive a global solution, whereas the later is solved by a proposed efficient subgradient algorithm extended from the simulated annealing-based Barzilai–Borwein algorithm. The proposed method obtains preferable localization performance with lower computational complexity. The convergence of our method in Lyapunov framework is also established. Simulation results demonstrate that the performance of PAMP method can be close to the optimality benchmark of Cramér–Rao Lower Bound.

MATCHED FIELD SOURCE LOCALIZATION WITH A HORIZONTAL LINE ARRAY

1994 ◽  
Vol 02 (03) ◽  
pp. 315-325
Author(s):  
N. R. CHAPMAN ◽  
M. L. YEREMY
Keyword(s):  
Source Localization ◽  
Sound Speed ◽  
Water Environment ◽  
Horizontal Line ◽  
Speed Profile ◽  
Field Source ◽  
Sound Speed Profile ◽  
Line Array ◽  
Localization Performance ◽  
Experimental Geometry

Matched field source localization performance is investigated for a source in aft endfire of a horizontal line array operating in a deep water environment. Simulations are used to investigate the performance for ideal conditions and in the presence of noise. In particular, the effects of uncertainty in experimental geometry and mismatch in sound speed profile are considered. It is shown that the performance is sensitive to the vertical tilt of the array for relatively small tilt angles of less than 5º. However, the horizontal array is robust to mismatch in the gradient of the sound speed profile at the bottom of the water column. The results of the simulations are interpreted in terms of the characteristics of acoustic propagation in the environment.

Robotic Sound Source Localization Using Bio-Inspired Acoustic Sensors

2012 ◽  
Author(s):  
Laith Sawaqed ◽  
Haijun Liu ◽  
Miao Yu
Keyword(s):  
Lower Bound ◽  
Source Localization ◽  
Sound Source ◽  
Structural Parameters ◽  
Sound Source Localization ◽  
Directional Microphones ◽  
Localization Method ◽  
Mechanical Coupling ◽  
Model Free ◽  
Localization Performance

In sound source localization, there is a fundamental size limit; the smaller the size, the smaller the directional cues that are relied on to pinpoint the sound source. As such, it is challenging to develop miniature sound source localization robotic system where space is too confined to employ conventional microphone arrays without compromising localization performance. Our previous studies show that through mechanical coupling with well-tuned structural parameters, directional microphones inspired by the parasitic fly Ormia ochracea can amplify the minute interaural time delay (ITD) by more than ten times, which enables the reduction of device size significantly while maintaining localization performance. In this paper, Cramer Rao lower bound (CRLB) is derived for the fly-ear inspired sensor and the conventional directional microphones to study the effects of mechanical coupling on the decrease of the theoretical lower bound of azimuth estimation. This improvement gives mobile robots the capability to reactively localize sound in an indoor environment. Using this miniature sensor, new sound source localization method is proposed to localize a stationary sound source in 2-D (azimuth and elevation). In the proposed sound localization method, Model-Free Gradient Descent (MFGD) optimization method, one of the main challenges is to choose the appropriate cost function to achieve minimum number of iterations and the smallest absolute error. To this end, different cost functions are proposed and investigated with different control schemes. Simulation results showed the ability of this technique to solve the ambiguity problem and localize the sound source.

scholarly journals Matched-field Source Localization with a Mobile Short Horizontal Linear Array in Offshore Shallow Water

2013 ◽  
Vol 38 (1) ◽  
pp. 105-113 ◽  
Author(s):  
Dexin Zhao ◽  
Zhiping Huang ◽  
Shaojing Su ◽  
Ting Li
Keyword(s):  
Shallow Water ◽  
Source Localization ◽  
Linear Array ◽  
Autonomous Underwater Vehicles ◽  
Field Source ◽  
Position Errors ◽  
Straight Line ◽  
Synthetic Test ◽  
Passive Source Localization ◽  
Localization Performance

Abstract Passive source localization in shallow water has always been an important and challenging problem. Implementing scientific research, surveying, and monitoring using a short, less than ten meter long, horizontal linear array has received considerable attention in the recent years. The short array can be conveniently placed on autonomous underwater vehicles and deployed for adaptive spatial sampling. However, it is usually difficult to obtain a sufficient spatial gain for localizing long-range sources due to its limited physical size. To address this problem, a localization approach is proposed which is based on matched-field processing of the likelihood of the passive source localization in shallow water, as well as inter-position processing for the improved localization performance and the enhanced stability of the estimation process. The ability of the proposed approach is examined through the two-dimensional synthetic test cases which involves ocean environmental mismatch and position errors of the short array. The presented results illustrate the localization performance for various source locations at different signal- to-noise ratios and demonstrate the build up over time of the positional parameters of the estimated source as the short array moves at a low speed along a straight line at a certain depth.

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