Bias Estimation in Sensor Networks

Bias Estimation for Decentralized Sensor Fusion

In multi-sensor data fusion (or sensor fusion), sensor biases (or offsets) often affect the accuracy of the correlation and integration results of the tracking targets. Therefore, to estimate and compensate the bias, several methods are proposed. However, most methods involve bias estimation and sensor fusion simultaneously by using Kalman filter after collecting the plot data together. Hence, ...

Target Tracking with Unknown Maneuvers Using Adaptive Parameter Estimation in Wireless Sensor Networks

Abstract- Tracking a target which is sensed by a collection of randomly deployed, limited-capacity, and short-ranged sensors is a tricky problem and, yet applicable to the empirical world. In this paper, this challenge has been addressed a by introducing a nested algorithm to track a maneuvering target entering the sensor field. In the proposed nested algorithm, different modules are to fulfill...

Location Estimation in Sensor Networks

Location Estimation in Sensor Networks

Bias Estimation in Asymmetric Packet-based Networks

In the context of the IEEE 1588 Precision Time Protocol (PTP), estimating the delay’s bias is a problem that appears in both one-way (using transparent devices) or two-way message exchange mechanisms. For estimating the offset via the two-way message exchange mechanism, it is usually being assumed that the expected value of delays in forward and reverse directions are equal with each other. How...

Coverage Quality in Visual Sensor Networks