ROBUST TARGET IDENTIFICATION

摘要

A target estimator that properly conditions measurement variates in the case of a series of sensor measurements collected against a target, a system model that captures visible and hidden stochastic information including but not limited to target state, target identity, and sensor measurements and that marginalizes measurement failure and a dynamic mixed quadrature expression facilitating real-time implementation of the estimator are presented.

主权项

1. A target identification system comprising:
a memory for storing data comprising:
a data structure stored in the memory, the data structure including:
a number of measurements of a target, each measurement from the number of measurements being observed at a predetermined time (zk);a number of target types (T);each one of the number of measurements, each one the number of target type and each one of one or more hidden states, each hidden state (xk) being characterized at the predetermined time, being correlated to one another; one or more processors operatively connected to the memory for storing data; the one or more processors being configured to: provide a first conditional probability distribution, a conditional probability of a target type given a number of measurements, defined inductively byp(Tz1,2,…,k)=p(zk,Tz1,2,…,k-1)∑T^p(zk,T^z1,2,…,k-1),Andp(zk,Tz1,2,…,k-1)=p(zkT,z1,2,…,k-1)p(Tz1,2,…,k-1)=p(Tz1,2,…,k-1)∑qk=0,1∫p(zk,xk,qkT,z1,2,…,k-1)xk=p(Tz1,2,…,k-1)∑qk=0,1∫p(zkT,xk,qk)p(xk,qkT,z1,2,…,k-1)xk where p(zk,i|T, xk) is a conditional probability of an ith measurement at a kth instance giving a target type T and hidden states at the kth instance, and p(T|z1, 2, . . . k-1) is a conditional probability distribution function of a target type, T, given the plurality of measurements at the k−1th time, z1, . . . k-1; ql={ql,1, ql,2, . . . , ql,F}: measurement quality at look l, E{ql,iql,j}i≠j=0; p(zk, xk, qk|T, z1, 2, . . . , k-1) is a conditional probability distribution function of a measurement at the kth instance, hidden states at the kth instance, measurement quality at the kth instance given a target type and the plurality of measurements at the k−1th time, z1, . . . k-1; p(zk|T, xk, qk) is a conditional probability distribution function of the measurement at the kth instance given a target type, the hidden states at the kth instance and the measurement quality at the kth instance; and p(xk, qk|T, z1, 2, . . . , k-1) is a conditional probability distribution function of the measurement at the kth instance and the measurement quality at the kth instance given a target type and the plurality of measurements at the k−1th time, z1, . . . k-1; and obtain an estimate of the target type from the first conditional probability.