Mobile emitter geolocation and tracking using TDOA and FDOA measurements

Authors:
Darko Mušicki;Regina Kaune;Wolfgang Koch
Affiliations:
Department of Electronic Information Systems Engineering, Hanyang University, Ansan, Kyunggido, Korea;Fraunhofer FKIE, Fraunhofer Institute for Communication, Information Processing and Ergonomics, Department SDF, Sensor Data and Information Fusion, Wachtberg, Germany;Fraunhofer FKIE, Fraunhofer Institute for Communication, Information Processing and Ergonomics, Department SDF, Sensor Data and Information Fusion, Wachtberg, Germany
Venue:
IEEE Transactions on Signal Processing
Year:
2010

Citing 3
Cited 0

Source Localization Using TDOA and FDOA Measurements in the Presence of Receiver Location Errors: Analysis and Solution

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Posterior Cramer-Rao bounds for discrete-time nonlinear filtering

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An accurate algebraic solution for moving source location using TDOA and FDOA measurements

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Abstract

This paper considers recursive tracking of one mobile emitter using a sequence of time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurement pairs obtained by one pair of sensors. We consider only a single emitter without data association issues (no missed detections or false measurements). Each TDOA measurement defines a region of possible emitter locations around a unique hyperbola. This likelihood function is approximated by a Gaussian mixture, which leads to a dynamic bank of Kalman filters tracking algorithm. The FDOA measurements update relative probabilities and estimates of individual Kalman filters. This approach results in a better track state probability density function approximation by a Gaussian mixture, and tracking results near the Cramér-Rao lower bound. Proposed algorithm is also applicable in other cases of nonlinear information fusion. The performance of proposed Gaussian mixture approach is evaluated using a simulation study, and compared with a bank of EKF filters and the Cramér-Rao lower bound.