Multitarget likelihood for Track-Before-Detect applications with amplitude fluctuations

Alexandre Lepoutre (1) , Olivier Rabaste (1) , François Le Gland (2)

1 ONERA - The French Aerospace Lab [Palaiseau]
2 ASPI - Applications of interacting particle systems to statistics

Track-Before-Detect methods jointly detect and track one or several targets from raw sensor measurements. They often require the computation of the measurement likelihood conditionally to the hidden state that depends on the complex amplitudes of the targets. Since these amplitudes are unknown and fluctuate over time this likelihood must be marginalized over the complex amplitude (i.e. phase and modulus). It has been demonstrated in [1] that this marginalization can be done analytically over the phase in the monotarget case. In this article, we first propose to extend the marginalization to the modulus in a monotarget setting, and we show that closed-forms can be obtained for fluctuations of type Swerling 1 and 3. Second, we demonstrate that, in a multitarget setting, a closed-form can be obtained for the Swerling 1 case. For Swerling 0 and 3 models, we propose some approximation to alleviate the computation. Since many articles consider the case of squared modulus measurements, we also consider this specific case in mono and multitarget settings with Swerling 0, 1 and 3 fluctuations. Finally, we compare the performance in estimation and detection for the different cases studied and we show the gain, both in detection and estimation, of the complex measurement method over the squared modulus method, for any fluctuation model.

Keywords: MULTIPLE HYPOTHESIS TRACKER (MHT); INFRARED SENSOR (IR); TRACK-BEFORE-DETECT

Domains: Electromagnetism

Alexandre Lepoutre, Olivier Rabaste, François Le Gland. Multitarget likelihood for Track-Before-Detect applications with amplitude fluctuations. IEEE Transactions on Aerospace and Electronic Systems, 2016, 52 (3), p. 1089-1107. ⟨10.1109/TAES.2016.140909⟩. ⟨hal-01393453⟩