loading page

Coherent long-time integration and Bayesian detection with Bernoulli track-before-detect
  • +1
  • Murat Uney ,
  • Paul Horridge ,
  • Bernard Mulgrew ,
  • Simon Maskell
Murat Uney
University of Liverpool, University of Liverpool

Corresponding Author:[email protected]

Author Profile
Paul Horridge
Author Profile
Bernard Mulgrew
Author Profile
Simon Maskell
Author Profile


We consider the problem of detecting small and manoeuvring objects with staring array radars. Coherent processing and long-time integration are key to addressing the undesirably low signal-to-noise/background conditions in this scenario and are complicated by the object manoeuvres. We propose a Bayesian solution that builds upon a Bernoulli state space model equipped with the likelihood of the radar data cubes through the radar ambiguity function. Likelihood evaluation in this model corresponds to coherent long-time integration. The proposed processing scheme consists of Bernoulli filtering within expectation maximisation iterations that aims at approximately finding complex reflection coefficients. We demonstrate the efficacy of our approach in a simulation example.
2023Published in IEEE Signal Processing Letters volume 30 on pages 239-243. 10.1109/LSP.2023.3253039