Implementation of 1D/2D/3D sensor data fusion in CASE_ATTI test-bed

Abder Rezak Benaskeur; Zoubeida Triki

doi:10.1117/12.487417

25 August 2003 Implementation of 1D/2D/3D sensor data fusion in CASE_ATTI test-bed

Abder Rezak Benaskeur, Zoubeida Triki

Proceedings Volume 5096, Signal Processing, Sensor Fusion, and Target Recognition XII; (2003) https://doi.org/10.1117/12.487417
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Fusion problem of dissimilar sensor data in the CASE_ATTI test-bed is considered. The sensors suite simulated includes an ESM sensor that reports bearing-only contacts, a 2D radar that reports range-bearing contacts, an IRST sensor that reports bearing-elevation contacts, and a 3D radar that reports full 3D contacts. To fuse all this information, CASE_ATTI is modified into a two-layer fusion architecture, with four sensor-level trackers and a central fusion node. Therefore, the fusion of all the dissimilar 1D, 2D and 3D tracks represents an important problem that this paper addresses. The important and directly related issue of tracking with angle-only reports is also addressed. The angle-only tracking represents an important issue in modern surveillance systems and has been extensively studied in recent years. Angle-only tracking systems are known to be unobservable unless the interceptor over-maneuvers the target. A divergence of the target state estimate may occur in the case of stationary or non-maneuvering interceptor. In this article, a new time alignment algorithm, that enhances stability, even for non-maneuvering interceptors, is developed. The proposed algorithm is based upon the modified spherical coordinate representation, but uses a different discretization approach that leads to a more stable behavior. Comparative scenario that illustrates the efficiency of the proposed architecture is presented.

Citation Download Citation

Abder Rezak Benaskeur and Zoubeida Triki "Implementation of 1D/2D/3D sensor data fusion in CASE_ATTI test-bed", Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); https://doi.org/10.1117/12.487417

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KEYWORDS

Sensors

Radar

Spherical lenses

Data fusion

Detection and tracking algorithms

Filtering (signal processing)

Electronic support measures

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