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Target detection and tracking is a well-established area of research. However, a majority of proposed solutions in existing literature rely on expensive and specialized sensors, which often have limited coverage. Using low cost sensor nodes is an attractive and complementary approach to scalable target detection and tracking applications. However, tracking(More)
In this position paper, we investigate the use of wireless sensor network (WSN) technology for ground surveillance. The goal of our project is to develop a prototype of WSN for outdoor deployment. We aim to design a system, which can detect and classify multiple targets (e.g., vehicles and troop movements), using inexpensive off-the-shelf wireless sensor(More)
The work reported in this paper investigates the performance of the Particle Filter (PF) algorithm for tracking a moving object using a wireless sensor network (WSN). It is well known that the PF is particularly well suited for use in target tracking applications. However, a comprehensive analysis on the effect of various design and calibration parameters(More)
The paper presents an algorithm for detection and a subsequent information gain driven search for an unaccounted point source of relatively low-level gamma radiation. Source detection and parameter estimation are carried out jointly in the Bayesian framework using a particle filter. The observer control vector consists of the next sensor location and the(More)
A typical sensor data processing sequence uses a detection algorithm prior to tracking to extract point-measurements from the observed sensor data. Track-before-detect (TkBD) is a paradigm which combines target detection and estimation by removing the detection algorithm and supplying the sensor data directly to the tracker. Various different approaches(More)
– Standard target state estimation schemes typically use detections as their source of measurements, which are produced by thresholding the output of a sensor's signal processing stage. This work exploits a track-before-detect (TBD) technique, which simultaneously detects and tracks a target without needing to threshold the sensor data. By removing the need(More)
In this paper, we present a comprehensive analysis of the performance of a wireless sensor network based target tracking system using the Particle Filter. In particular, we evaluate the effect ofvarious network design parameters such as the number ofnodes, number ofgenerated particles, and sampling interval on the tracking accuracy and computation time of(More)
  • Mark Rutten
  • 2013
A square-root Kalman filter propagates the square-root (often the Cholesky factor) of the state covariance, rather than the full covariance matrix. Propagating these factors offers both computational efficiencies and greatly improved numerical properties. This paper introduces a new method of implementing the square-root unscented filter and the square-root(More)
Over-the-horizon radar (OTHR) and microwave radar networks can together generate track data over a wide surveillance region. However the data is often subject to ambiguity and uncertainty due to the complexities of the HF signal propagation environment, which give rise to multipath OTHR tracks, as well as ambiguities in target associations between multiple(More)