Channel energy based estimation of target trajectories using distributed sensors with low communication rate

Abstract--Sensor localization using channel energy measurements of distributed sensors has been studied in various scenarios. However, it is usually assumed that the target does not move significantly during the time needed to collect and process the data from the sensors. We want to estimate the trajectory of a moving target using a network of distributed sensors that measure only the received signal strength (RSS), sampled and as a function of time, without knowledge of the target amplitude/source level. To reduce the communication load, sensors communicate a reduced data set to the fusion center (FC), generated through local processing. It consists of three characteristic parameters: i) the maximum measured amplitude, corresponding to the closest-point-of-approach (CPA); ii) the corresponding time index; and iii) the time it takes for the amplitude to diminish by 6 dB relative to the CPA. To generate the reduced data sets, each sensor calculates a local maximum likelihood (ML) estim...

• Type: Journal
• Year: 2010
• Where: TSP
• Authors: Christian R. Berger, Sora Choi, Shengli Zhou, Peter Willett
• Keywords: Artificial Intelligence, Communication Load, Maximum Measured Amplitude, Sensors, TSP 2010