Multi-sensor track-before-detect for complementary sensors

Abstract

A typical sensor data processing sequence uses a detection algorithm prior to tracking to extract point measurements from the observed sensor data. Track-before-detect (TkBD) is a paradigm which combines target detection and estimation by removing the detection algorithm and supplying the sensor data directly to the tracker. It is a non-linear non-Gaussian estimation problem, typically requiring numerical methods. While, in general, TkBD schemes are a more computationally expensive method of tracking, removal of the detection threshold allows for the detection and tracking of targets at much lower signal-to-noise ratios. In this paper we develop TkBD algorithms for multiple asynchronous dissimilar sensors. The problem of radar and IRST fusion is presented as an example and the performance of TkBD is compared with a Multi-Hypothesis Tracker. In the example, the TkBD algorithm is able to utilise IRST data to produce high accuracy in azimuth and elevation well beyond the conventional operating range of the sensor.