Single-platform passive emitter localization with bearing and Doppler-shift measurements using pseudolinear estimation techniques

The maximum-likelihood (ML) estimator for single-platform Doppler-bearing emitter localization does not admit a closed-form solution and must be implemented using computationally demanding iterative numerical search algorithms. The iterative ML solution is vulnerable to convergence problems due to the nonconvex nature of the ML cost function and the threshold effect. To alleviate these problems, this paper presents new closed-form Doppler-bearing emitter localization algorithms in the 2D-plane based on pseudolinear estimation techniques; namely, the pseudolinear estimator (PLE), the bias-compensated PLE and the weighted instrumental variable (WIV) estimator. The bias-compensated PLE aims to remove the instantaneous estimation bias inherent in the PLE. The WIV estimator incorporates the bias-compensated PLE to achieve an asymptotically unbiased estimate of the emitter position. The proposed WIV estimator is proved to be asymptotically efficient for sufficiently small measurement noise. Through simulation examples its performance is shown to be almost identical to that of the ML estimator, exhibiting small bias and approaching the Cramer-Rao lower bound at moderate noise levels. HighlightsThe problem of single-platform Doppler-bearing emitter localization is considered.New localization algorithms are proposed based on pseudolinear estimation technique.Proposed algorithms are closed-form with low complexity and inherent stability.The proposed WIV estimator enjoys the desirable property of asymptotic unbiasedness.It is analytically shown to be asymptotically efficient for small measurement noise.

[1]  Kutluyil Dogançay,et al.  UAV Path Planning for Passive Emitter Localization , 2012, IEEE Transactions on Aerospace and Electronic Systems.

[2]  NguyenNgoc Hung,et al.  Single-platform passive emitter localization with bearing and Doppler-shift measurements using pseudolinear estimation techniques , 2016 .

[3]  Kutluyil Dogançay,et al.  On the bias of linear least squares algorithms for passive target localization , 2004, Signal Process..

[4]  Christoph J. Scriba,et al.  André Weil: Number Theory: An approach through history. From Hammurapi to Legendre. Boston/Basel/Stuttgart: Birkhäuser 1983. XXI und 375 Seiten, Ln., DM 74,-. , 1987 .

[5]  Kutluyil Dogançay,et al.  3D Pseudolinear Target Motion Analysis From Angle Measurements , 2015, IEEE Transactions on Signal Processing.

[6]  Sandra Lowe,et al.  Probability A Graduate Course , 2016 .

[7]  Andreas F. Molisch,et al.  Accurate Passive Location Estimation Using TOA Measurements , 2012, IEEE Transactions on Wireless Communications.

[8]  K. C. Ho,et al.  A simple and efficient estimator for hyperbolic location , 1994, IEEE Trans. Signal Process..

[9]  P. Kumar,et al.  Theory and practice of recursive identification , 1985, IEEE Transactions on Automatic Control.

[10]  J. Mendel Lessons in Estimation Theory for Signal Processing, Communications, and Control , 1995 .

[11]  Fred A. Dilkes,et al.  Doppler Frequency Geolocation of Uncooperative Radars , 2007, MILCOM 2007 - IEEE Military Communications Conference.

[12]  C. Jauffret,et al.  Target motion analysis with bearings and frequencies measurements via instrumental variable estimator (passive sonar) , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[13]  K. Doğançay Emitter localization using clustering-based bearing association , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[14]  K. C. Ho Bias Reduction for an Explicit Solution of Source Localization Using TDOA , 2012, IEEE Transactions on Signal Processing.

[15]  K. Gong,et al.  Fundamental properties and performance of conventional bearings-only target motion analysis , 1984 .

[16]  K. Gong,et al.  Position and Velocity Estimation Via Bearing Observations , 1978, IEEE Transactions on Aerospace and Electronic Systems.

[17]  J. Cadre,et al.  On the convergence of iterative methods for bearings-only tracking , 1999 .

[18]  Kutluyıl Doğançay,et al.  Bias compensation for the bearings-only pseudolinear target track estimator , 2006, IEEE Transactions on Signal Processing.

[19]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[20]  C. Jauffret,et al.  Observability in passive target motion analysis , 1996 .

[21]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[22]  K. Becker An efficient method of passive emitter location , 1992 .

[23]  K. C. Ho,et al.  An accurate algebraic solution for moving source location using TDOA and FDOA measurements , 2004, IEEE Transactions on Signal Processing.

[24]  Kutluyil Dogançay Passive emitter localization using weighted instrumental variables , 2004, Signal Process..

[25]  Kutluyil Dogançay,et al.  Optimal angular sensor separation for AOA localization , 2008, Signal Process..

[26]  Frankie K. W. Chan,et al.  Best linear unbiased estimator approach for time-of-arrival based localisation , 2008 .

[27]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[28]  Don Torrieri,et al.  Statistical Theory of Passive Location Systems , 1984, IEEE Transactions on Aerospace and Electronic Systems.

[29]  Kutluyil Dogançay,et al.  Bearings-only target localization using total least squares , 2005, Signal Process..

[30]  André Weil,et al.  Number Theory: An approach through history From Hammurapi to Legendre , 1984 .

[31]  Yiu-Tong Chan,et al.  Bearings-only and Doppler-bearing tracking using instrumental variables , 1992 .

[32]  K. C. Ho,et al.  An asymptotically unbiased estimator for bearings-only and Doppler-bearing target motion analysis , 2006, IEEE Transactions on Signal Processing.

[33]  Weihua Zhuang,et al.  Hybrid TDOA/AOA mobile user location for wideband CDMA cellular systems , 2002, IEEE Trans. Wirel. Commun..