Event Details
Expanding Window Dynamic Programming Based Track-Before-Detect.
Presenter: Mostafa Elhoshy
Supervisor:
Date: Wed, July 17, 2019
Time: 08:30:00 - 09:30:00
Place: EOW 230
ABSTRACT
Target detection is an important task in radar signal processing and is typically the first step. This determines whether a target is present in a resolution cell by comparing the decision statistic with a threshold. Conventional algorithms make a detection decision each frame and then use the results for tracking. Detection and tracking of weak fluctuating targets using dynamic programming (DP) based track-before-detect (TBD) are considered. The clutter is modeled using a Weibull distribution and the well-known Swerling type 0, 1 and 3 targets are addressed.
A novel expanding window multiframe (EW-TBD) technique is presented to improve the detection performance with reasonable computational complexity compared to batch processing. It is shown that EW-TBD has lower complexity than existing multiframe processing techniques. Simulation results are presented which confirm the superiority of the proposed expanding window technique in detecting targets even when they are not present in every scan in the window. In addition, the throughput of the proposed technique is higher than with batch processing.