Method for tracking moving objects

Communications: directive radio wave systems and devices (e.g. – Return signal controls radar system – Receiver

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G01S 1366

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active

055371183

ABSTRACT:
The tracking of moving objects on land, in the air or at sea is effected by means of one or more sensors (S.sub.j.sup.1). The observation space of each sensor is divided into resolution cells (X.sup.1h) forming a grid. The sensors of the same grid are grouped together.
A probability estimate (.beta.k) for a moving object being in a cell (Xk) which is an intersection of the resolution cells (X.sup.1h) is produced. For this purpose, the starting points are signals (M.sub.j.sup.1h) delivered by the sensors (S.sub.j.sup.1) and previously selected according to windowing criteria, sets of pairs (F.sub.i (M.sub.j.sup.1h)D.sub.ij.sup.1h) stored in memories (1) and coming from a prior supervised statistical learning, and tracking coefficients (.alpha.k) delivered by an adaptive tracking filter (4) of the PDAF type. After application of this probability (.beta.k) to the adaptive tracking filter (4), there is obtained on the one hand an estimated status (X*,P*) affording a trajectory prediction (x,S) for at least one moving object and, on the other hand, the windowing criterion is adjusted.

REFERENCES:
patent: 5392225 (1995-02-01), Ward
IEEE TAES, vol. 29, No. 2, Apr. 1993, NEW YORK, NY, USA; pp. 352-363; B. ZHOU ET N. K. BOSE "Multitarget tracking in clutter: fast algorithms for data association".
ICASSP 91 S2 VSLI U, vol. 2, 14 Mai 1991, THE SHERATON CENTRE HOTEL & TOWERS, TORONTO, ONTARIO, CANADA; pp. 1437-1440 SERGE PROSPERI "New passive tracking algorithms using power information with application to passive sonar".
IEEE TAES, vol. 29, No. 4, Sep. 1993, NEW YORK, NY, USA, pp. 1275-1286; JEAN DEZERT ET YAAKOV BAR SHALOM "Joint probabilistic data association for autonomous navigation".

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