Multistatic Post-Track Classification using a Target Strength Function

摘要

The Specular-Cued Surveillance Web (SPECSweb) multistatic tracker effectively reduces false track rate through the use of two amplitude thresholds. A high threshold is used to identify the occurrence of high-strength specular detection cues for track initiation. A low threshold is used for selective extraction of additional detections for track extension forward and backward in time. This approach significantly reduces the node-to-fusion-center communication loading requirements as well as reducing the output false track rate. At the time of the specular-cued track initiation, a historical (back)-track is reconstructed and output. In some cases, there may still be false tracks at the tracker output. We demonstrate a post-tracking classification method based on the expected Target Strength (TS) function, which identifies and further reduces residual false tracks. Cylindrical targets exhibit aspect-dependent TS which produces variations in the SNR levels of detected echoes. The multistatic tracker output provides estimates of target heading and therefore also of target aspect angle. The level variations of contact-sets corresponding to track segments are correlated with the expected TS function to provide a classification score. The method is shown to have potential in reducing false tracks when applied to the PACsim simulated data sets of the Multistatic Tracking Working Group (MSTWG).