Proceedings Article | 6 July 1994
Proc. SPIE. 2235, Signal and Data Processing of Small Targets 1994

KEYWORDS: Radar, Signal to noise ratio, Super resolution, Detection and tracking algorithms, Doppler effect, Sensors, Optical resolution, Modulation transfer functions, Probability theory, Environmental sensing

Sensor resolution is crucial for the success of tracking in a dense multiple target environment. The probability of resolution (P_{R}) and the probability of correct data association (P_{DA}) are computed as a function of: (1) average object separation, (2) sensor resolution, and (3) one-sigma prediction error, for sensor measurements with dimensions n equals 1, 2, 3, ... . The values of P_{R} and P_{DA} are plotted versus the average object separation normalized by the sensor resolution, parameterized by the one-sigma prediction error, for values of n equals 1, 2, 3, ... . By inspection of these curves, it is obvious that P_{R} is less than P_{DA} for n equals 1, 2, 3, ... for any values of average object separation and sensor resolution, for almost any practical value of one-sigma prediction error of interest. This means that sensor resolution is a more important issue than data association in most practical applications. Nevertheless, 99 percent of the literature on multiple target tracking has ignored the issue of resolution.