An Asymptotically Efficient Estimator for TDOA and FDOA Positioning of Multiple Disjoint Sources in the Presence of Sensor Location Uncertainties
Ming Sun, K. C. Ho
Abstract
Ming Sun, K. C. Ho
Abstract
This correspondence considers the problem of locating multiple disjoint sources using time differences of arrival (TDOAs) and frequency differences of arrival (FDOAs) in the presence of sensor position and velocity errors. Previous work applies to one source only with suboptimum performance for near source, or requires joint estimation of the source and sensor locations that could be computation demanding. Through nonlinearly transforming the measurements and converting them with respect to the inaccurate sensor locations, we have developed an algebraic solution to this problem. The solution is shown analytically to achieve the Cramér–Rao lower bound (CRLB) performance over small noise region and does not require joint estimation with sensor locations.
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This correspondence considers the problem of locating multiple disjoint sources using time differences of arrival (TDOAs) and frequency differences of arrival (FDOAs) in the presence of sensor position and velocity errors. Previous work applies to one source only with suboptimum performance for near source, or requires joint estimation of the source and sensor locations that could be computation demanding. Through nonlinearly transforming the measurements and converting them with respect to the inaccurate sensor locations, we have developed an algebraic solution to this problem. The solution is shown analytically to achieve the Cramér–Rao lower bound (CRLB) performance over small noise region and does not require joint estimation with sensor locations.
Key concepts: Multilateration, Cramér–Rao bound, Estimator, Disjoint sets, FDOA, Algorithm, Upper and lower bounds, Computer science