Reliability of PDA based Target Tracking in Clutter

Data association target tracking algorithms assume knowledge of target detection probability and sensor measurement noise. They are unknown and/or variable. Target signal is unknown due to unknown and time-varying target radar cross section as well as multi-path signal attenuation and variable propagation signal losses. Noise power is unknown due to the presence of unknown clutter signal whose residual power will increase the detection noise level, electronic counter-measures will also increase the noise power. The probability of target detection and the sensor measurement noise are affected by the (unknown) signal to noise ratio. Sensor measurement noise is also affected by proximity of large clutter reflectors due to the finite resolution capabilities of the sensor. This paper is a study of the effects of unknown probability of detection and sensor noise to the false track discrimination capabilities of IPDA and IMM-PDA target tracking algorithms

Target Track Initiation Comparison and Optimization

This paper proposes a procedure for comparison of target tracking filters in cluttered environment, using simulated experiments. Important simulation issues, including track generation and retention across simulation runs and true track definition are discussed. False track discrimination is identified as an important target tracking filter performance measure. This measure has two components; confirmed true track statistics and confirmed false track statistics. In order to meaningfully compare false track discrimination capabilities of target tracking filters, we suggest optimizing true track statistics, while using false track statistics as the optimization constrains. The optimization procedure is described, and the importance of correct parameter selection is illustrated