SIMULTANEOUS LOCALIZATION AND TRACKING IN AN AD HOC SENSOR NETWORK

Make a note of similarity between SLAM and localization, tracking. We demonstrate that it is possible to achieve accurate localization while target tracking in a randomly placed wireless sensor network composed of inexpensive components of limited accuracy. We present an algorithm for creating such a coordinate system without the use of global control, globally accessible beacon signals, or accurate estimates of inter-sensor distances. The coordinate system is robust and automatically adapts to the failure or addition of sensors. The algorithm learns from observations of local events, events that can be sensed in a particular neighborhood. Tracking improves over time providing a measurable error that can also be used to guide further exploration. The algorithm is based upon a general parameter estimation framework that easily incorporates a priori knowledge, provides error estimates on all measurements, and allows for well founded outlier rejection. Furthermore, this approach can be generalized to also simultaneously calibrate sensors and perform time synchronization and its coordinate system can optionally be aligned to surveyed positions.