Bayesian multi-target localization using blocking statistics in multipath environments

Passive localization based on distributed MIMO radar has a wide variety of applications ranging from security/military to consumer support. This paper considers the problem of localizing a (passive) target through time-of-arrival measurements from a number of (distributed) single-antenna transmitters to distributed receivers in the presence of objects that can block the line of sight between transmitter/receiver and target. The key effect investigated in this paper is the correlation of the blocking between an object and different transmitters/receivers. We formulate the problem in a Bayesian framework and suggest a sub-optimum but efficient algorithm to solve this problem; simulations show considerably better performance than can be achieved by ignoring the blocking statistics.