General solution for asynchronous sensors bias estimation

In multisensor systems, the measurements reported by local sensors are usually not time aligned or synchronous due to different data rates. A novel algorithm, based on Kalman filter combined with pseudomeasurement and equivalent bias, is proposed to solve a general bias estimate problem in asynchronous sensors systems. The pseudomeasurement equation of sensor biases is obtained by linearizing the last measurements provided by asynchronous sensors to remove the target state. The equivalent bias equation in each sampling interval of fusion center is derived from the bias dynamic equation of asynchronous sensors with different rates. Monte Carlo simulation results show that the Cramer-Rao lower bound (CRLB) is achievable, i.e., the new algorithm is statistically efficient.

[1]  Chongzhao Han,et al.  Optimal batch asynchronous fusion algorithm , 2005, IEEE International Conference on Vehicular Electronics and Safety, 2005..

[2]  J.E. Gray,et al.  Theory of distributed estimation using multiple asynchronous sensors , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[3]  T. Kirubarajan,et al.  Multisensor multitarget bias estimation for general asynchronous sensors , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[4]  Thia Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software , 2001 .

[5]  R. Bishop,et al.  Solution to a multisensor tracking problem with sensor registration errors , 1999 .

[6]  Y. Bar-Shalom,et al.  Exact multisensor dynamic bias estimation with local tracks , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[7]  Branko Ristic,et al.  Sensor registration in ECEF coordinates using the MLR algorithm , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.

[8]  S. Challa,et al.  Joint sensor registration and track-to-track fusion for distributed trackers , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[9]  Yaakov Bar-Shalom,et al.  Tracking with debiased consistent converted measurements versus EKF , 1993 .

[10]  Henry Leung,et al.  Simultaneous registration and fusion of multiple dissimilar sensors for cooperative driving , 2004, IEEE Transactions on Intelligent Transportation Systems.

[11]  Behzad Moshiri,et al.  A new algorithm for general asynchronous sensor bias estimation in multisensor-multitarget systems , 2007, 2007 10th International Conference on Information Fusion.