Integration of complementary detection-localization systems-an example

The integration (or fusion) of two or more detection-localization systems often results in performance improvement, especially if they are complementary to each other. On the other hand, the cost of integration in additional signal processing and overhead may be considerable. As a figure of merit for this tradeoff, the authors propose the dB-gain-to-cost ratio and illustrate its evaluation by using a simple example. The example consists of a pair of detection-localization systems which have complementary features. One has higher resolution that the other, but is more susceptible to random disturbances. The author models the first as a system which detects a signal in multiplicative and additive random disturbances and additive white noise. Thus, one main result is the derivation of the maximum likelihood detector under these disturbances. In the second system, the author assumes the random disturbances to be negligible. Hence, the maximum likelihood detector is the matched filter. Input data to both systems are two-dimensional arrays of real numbers corresponding to the same physical area under observation where the second data array has a coarser grid than the first, thus yielding poorer resolution. The detection probabilities, in terms of which the dB-gains are computed, are evaluated by Monte Carlo simulation