Space-invariant projection method for multi-target positioning

This paper discusses the positioning method of the sensor network in the viewpoint of the imaging technique. We find that similarly to the GPS system, sensor networks can position and track targets in 3D space. In multitarget case, the data association problem is crucial and extremely complex, which can be overcome via the projection strategy. In the face of a vast surveillance region, the space-variant feature of the system resolution makes it difficult to partition the image space soundly. By mapping the geographic space into the BR space, one can partition the 3-D space exhaustively and exclusively.

[1]  Elliott D. Kaplan Understanding GPS : principles and applications , 1996 .

[2]  Jun Shi,et al.  Streaming BP for Non-Linear Motion Compensation SAR Imaging Based on GPU , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  Z. H. Cho,et al.  Ultra Fast Symmetry and SIMD-Based Projection-Backprojection (SSP) Algorithm for 3-D PET Image Reconstruction , 2007, IEEE Transactions on Medical Imaging.

[4]  J. Schindler,et al.  Multi-Target/Multi-Sensor Tracking using Only Range and Doppler Measurements , 2009, IEEE Transactions on Aerospace and Electronic Systems.

[5]  Mengdao Xing,et al.  High-Resolution Three-Dimensional Imaging of Spinning Space Debris , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Weihong Zhang,et al.  A Probabilistic Approach to Tracking Moving Targets With Distributed Sensors , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.