Distributed localization using acoustic Doppler

It is well-known that the motion of an acoustic source can be estimated from Doppler shift observations. It is however not obvious how to design a sensor network to efficiently deliver the localization service. In this work a rather simplistic motion model is proposed that is aimed at sensor networks with realistic numbers of sensor nodes. It is also described how to efficiently solve the associated least squares optimization problem by Gauss-Newton variable projection techniques, and how to initiate the numerical search from simple features extracted from the observed frequency series. The methods are evaluated by Monte Carlo simulations and demonstrated on real data by localizing an all-terrain vehicle. It is concluded that the processing components included are fairly mature for practical implementations in sensor networks. HighlightsWe consider a distributed network of acoustic Doppler sensors.We model an acoustic source motion with parameterized models.The motion parameters are estimated based on the Doppler.A tailored Gauss-Newton algorithm with robust initialization is described.Computational and numerical efficiencies are showed for realistic noise levels.

[1]  Sailes K. Sengijpta.  Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[2]  Y. Chan,et al.  Sequential localization of a radiating source by Doppler-shifted frequency measurements , 1992 .

[3]  Ehud Weinstein,et al.  Passive Array Tracking of a Continuous Wave Transmitting Projectile , 1980, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Mark A. Richards,et al.  Fundamentals of Radar Signal Processing , 2005 .

[5]  T. Pàmies,et al.  Aircraft tracking by means of the Acoustical Doppler Effect , 2013 .

[6]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[7]  Brian D. O. Anderson,et al.  Analysis of target velocity and position estimation via doppler-shift measurements , 2011, 2011 Australian Control Conference.

[8]  N. A. Suslov,et al.  Fundamentals of Radar , 1971 .

[9]  Joseph Statman,et al.  Parameter Estimation Based on Doppler Frequency Shifts , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[10]  Fredrik Gustafsson,et al.  Multi-target tracking with PHD filter using Doppler-only measurements , 2014, Digit. Signal Process..

[11]  Gene H. Golub,et al.  The differentiation of pseudo-inverses and non-linear least squares problems whose variables separate , 1972, Milestones in Matrix Computation.

[12]  Y. Chan.  A 1-D search solution for localization from frequency measurements , 1994 .

[13]  K. S. Arun,et al.  Least-Squares Fitting of Two 3-D Point Sets , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  D. Torney,et al.  Localization and Observability of Aircraft via Doppler Shifts , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[15]  Fredrik Gustafsson,et al.  Target Tracking With Particle Filters Under Signal Propagation Delays , 2011, IEEE Transactions on Signal Processing.

[16]  B. Ferguson.  A ground-based narrow-band passive acoustic technique for estimating the altitude and speed of a propeller-driven aircraft , 1992 .

[17]  Linda Kaufman,et al.  A Variable Projection Method for Solving Separable Nonlinear Least Squares Problems , 1974 .

[18]  Arnold Neumaier,et al.  Introduction to Numerical Analysis , 2001 .

[19]  Begnaud Francis Hildebrand,et al.  Introduction to numerical analysis: 2nd edition , 1987 .

[20]  Fredrik Gustafsson,et al.  Acoustic source localization in a network of Doppler shift sensors , 2013, Proceedings of the 16th International Conference on Information Fusion.

[21]  R. J. Webster.  An Exact Trajectory Solution from Doppler Shift Measurements , 1982, IEEE Transactions on Aerospace and Electronic Systems.