Histogram‐PMHT for fluctuating target models. Issue 8 (9th June 2017)

• Record Type: Journal Article
• Authors: Gaetjens, Han X.; Davey, Samuel J.; Arulampalam, Sanjeev; Fletcher, Fiona K.; Lim, Cheng‐Chew
• Is Part Of: IET radar, sonar & navigation. Volume 11:Issue 8(2017)
• Page Start: 1292
• Page End: 1301
• Publication Date: 2017-06-09
• Subjects: object tracking -- stochastic processes; fluctuating target models -- histogram PMHT -- histogram probabilistic multihypothesis tracker -- H‐PMHT -- multitarget tracking approach -- track‐before‐detect problem -- multinomial measurement model -- target amplitude -- Poisson mixture process -- fluctuating target amplitudes -- signal‐to‐noise ratio estimation; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2016.0618
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : The histogram‐probabilistic multi‐hypothesis tracker (H‐PMHT) is an efficient multi‐target tracking approach to the track‐before‐detect problem. A fundamental feature of the H‐PMHT is the discretisation of the energy in the sensor data and the assumption of a multinomial measurement model on the resulting image. A problem with the H‐PMHT is that the multinomial measurement model fails to account for fluctuations in the target amplitude, which can degrade performance in realistic sensing conditions. The authors propose an alternative measurement model based on a Poisson mixture process to allow for fluctuating target amplitudes. Simulations show that this new approach, referred to as the Poisson H‐PMHT, gives more accurate signal‐to‐noise ratio estimates than the standard H‐PMHT, particularly for scenarios featuring targets with fluctuating amplitude.