Design of Suboptimal Matched Filters for Three-Dimensional Moving Target Detection

摘要

The optimal detection of a three-dimensional moving target calls for the classical technique of matched filtering. If a target is modeled as a moving point source with unknown velocity, then the velocity alone determines the shape of the observed signal. Thus, target velocity is a parameter that completely characterizes the matched filter. We will designate these types of matched filters to be the assumed velocity filters (AVFs) to emphasize the velocity parameter. Like most matched filtering techniques where the signal parameters range in a continuum, the AVF must be implemented suboptimally by quantizing the velocity space. In this report we will use a loss factor that measures the average loss of signal-to-noise ratio (SNR) at the output of the matched filter due to mismatch of filter parameters. The loss factor can be used as a criterion for partitioning the velocity space. We will show that, with a fixed loss factor, the number of filters required for coverage increases linearly as the span of the two-dimensional velocity space increases quadratically. The rate of increase is further reduced when the loss factor is made proportional to expected target angular speed.