1. A method for tracking the trajectory of moving objects, of the type in which: a) one or more sensors (S.sub.j.sup.1) are provided, which deliver signals (M.sub.j.sup.1h) relating to the presence of at least one moving object, with reference to a known division of space, peculiar to each group of sensors, in so-called spatial resolution cells (X.sup.1h); b) by means of logic tests peculiar to each sensor, some of these signals (M.sub.j.sup.1h) are selected in accordance with a chosen windowing criterion, relating to the resolution cells (X.sup.1h); c) an estimate is worked out of the probability (.beta.k) that a moving body has of being in a cell (Xk) which is the intersection of the resolution cells (X.sup.1h) peculiar to each sensor (S.sub.j.sup.1), according to the signals selected at b), and trajectory tracking data (.alpha.k); d) this probability (pk) is applied to an adaptive tracking filter (4), the output of this filter (4) supplying an estimated status (X*,P*) and affording a trajectory prediction (x,S) for at least one moving object; and e) the chosen windowing criterion is adjusted according to this trajectory prediction (x,S), step c) comprising: c1) the prior storage in memory of n sets of J distribution functions F.sub.i (M.sub.j.sup.1h), these n sets relating respectively to n identities H.sub.i of indexed moving objects (i=1 to n; j=1 to J, each of these functions (F.sub.i (M.sub.j.sup.1h) representing the a priori probability (P(M.sub.j.sup.1h /H.sub.i)) of observing the measurement (M.sub.j.sup.1h) in the resolution cell (X.sup.1h) of the sensor (S.sub.j.sup.1) when a moving object of identity (H.sub.i) is presented to this sensor, and having a coefficient (D.sub.ij.sup.1h) representing the degree of confidence given thereto; c2) the determination, from each measurement (M.sub.j.sup.1h) and the pairs (F.sub.i (M.sub.j.sup.1h), D.sub.ij.sup.1h) stored in memories, of orders of likelihood (A.sub.ij.sup.1h, B.sub.ij.sup.1h), and this for all the identities (H.sub.i) indexed, where A.sub.ij.sup.1h represents the likelihood ratio between the cases "there is a moving object of identity H.sub.i in cell X.sup.1h " and "no moving object of identity H.sub.i is present in the cell X.sup.1h ", whilst B.sub.ij.sup.1h represents an uncertainty factor for A.sub.ij.sup.1h ; c3) the merging, for each resolution cell (X.sup.1h) and each identity of moving objects (H.sub.i), of these pairs of orders of likelihood (A.sub.ij.sup.1h, B.sub.ij.sup.1h) obtained for all the sensors (S.sub.j.sup.1) in the same alignment group, into a single pair of likelihood (A.sub.i.sup.1h, B.sub.i.sup.1h); c4) the calculation, from the likelihoods (A.sub.i.sup.1h, B.sub.i.sup.1h) relating to a first resolution cell (X.sup.1h), of the likelihood (Q.sup.1h) for there being in this cell (X.sup.1h) a moving object of the same identity as the moving object being tracked; c5) the calculation, from the likelihoods (Q.sup.1h) of each group of sensors, for each cell (Xk), the intersection of the resolution cells (X.sup.1h) in question, of the likelihood (Qk) of there being in this box (Xk) a moving object of the same identity as the moving object being tracked; and c6) the calculation, from the values (Qk) and tracking coefficients (.alpha.k) delivered by the adaptive tracking filter (4a), for each cell (Xk), of the a posteriori probability (.beta.K) that the moving body being tracked is in this cell (Xk).