Sensor scheduling simulations and results

Here we discuss simulations for sensor scheduling problems over up to two epochs into the future. The difficulties here reside in the design of the cost function and tracking of the scene. Our aim here is to show that sensor scheduling does, at least in simulation, achieve performance improvement. 

A brief description of the tracking and waveform scheduling aspects of the scheme is as follows  

Waveform Scheduling The choice of measurement is made using the control variable n(k). In fact two choices are made at each epoch, the target to be measured and the waveform used. The waveforms impinge on the measurement process through the covariance matrix of the noise In this model, the sensor is characterised 

We have compared one-step and two-step ahead scheduling using two performance measures. The first is the root mean square error of the track estimation this is a fairly obvious measure of the performance of the tracker. The second measure was the number of track updates. Since the sensor is managed in such a way that track updating is done only when the predicted track error exceeds a threshold, this also gives a measure of how far the estimation process is diverging from the actual target state. 

The next series of experiments is focused on how the choice of waveform libraries affect the problem of tracking of maneuvering targets. 

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