Situation assessment for aggregated vehicle merging at an unknown location

Kanupriya Salaria; Suman Das; Michael Hinman; John Salerno; Li Bai

doi:10.1117/12.606013

25 May 2005 Situation assessment for aggregated vehicle merging at an unknown location

Kanupriya Salaria, Suman Das, Michael Hinman, John Salerno, Li Bai

Proceedings Volume 5809, Signal Processing, Sensor Fusion, and Target Recognition XIV; (2005) https://doi.org/10.1117/12.606013
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

This paper introduces the merge at a point (MAP) algorithm to detect the vehicles convoys whose destination locations are unknown. The algorithm will predict the merged vehicles identification numbers in an iterative manner. We applied this method using the simulated Ground Moving Target Indicator (GMTI) data. The technique is similar to the dead reckoning and Kalman filtering algorithms. This algorithm consists of following procedures: 1) approximates the destination locations for each vehicle using its tracks, 2) validates what vehicles are going to merge at these predicted destination locations using the minimum error solution (MES), and 3) predicts the future destination locations where the vehicles will be merged at for the next iteration. This algorithm will be iteratively processed until predicted destination locations converge. We can use this algorithm to associate the vehicles that will merge to some unknown destination locations. It also has the potential to identify the convoy names and the threats associated with these vehicle groups.

Citation Download Citation

Kanupriya Salaria, Suman Das, Michael Hinman, John Salerno, and Li Bai "Situation assessment for aggregated vehicle merging at an unknown location", Proc. SPIE 5809, Signal Processing, Sensor Fusion, and Target Recognition XIV, (25 May 2005); https://doi.org/10.1117/12.606013

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