Section: New Results

Objective 2 – High dimensional filtering

The work presented in [10] is about solutions for 2D multitarget tracking from image observations including its application on radar data and results on simulated data. Tracking from image observations rather than from detected points is often referred to as track–before–detect (TBD). The objective is to capture targets with a low signal–to–noise ratio (SNR) which would not be detected or tracked after data thresholding. The highly nonlinear filtering equations are approximated using a particle filter implementation. This nonlinearity emerges from the observation function which relies on the radar treatment chain, involving matched filtering of a chirp signal, and beamforming achieved from a linear phased array, leading to the raw data image. Amplitudes and phases of target–returned signals are considered as temporally fluctuating, random and unknown, creating non–deterministic contributions of the targets to the signal to deal with.