Name
Abstract | ||
|---|---|---|
This paper is concerned with performing the measurement-to-measurement association and bias estimation jointly in the presence of missed detections. An integrated mix integer programming (MINLP) model is established to determine the correspondence between local measurements and estimate sensor biases simultaneously. An alternation optimization mechanism is employed to solve the complicated MINLP model. A recursive version for bias estimation is developed that provides an access to deal with the measurement data sequentially. Monte Carlo simulation results are presented to illustrate our findings, as also demonstrating the effectiveness of the proposed approach. |
Year | Venue | Keywords |
|---|---|---|
2014 | Fusion | sensor bias estimation,minlp model,mixed integer nonlinear programming (minlp),data association,monte carlo simulation,integer programming,alternation optimization mechanism,linear programming,integrated mix integer programming model,monte carlo methods,measurement-to-measurement association,integrated data association,missed detections,sensor biases,bias estimation,multisensor fusion system,sensor fusion,optimization,measurement uncertainty,time measurement,estimation,azimuth |
Field | DocType | Citations |
Mathematical optimization,Monte Carlo method,Computer science,Integer programming,Data association,Recursion,Alternation (linguistics) | Conference | 1 |
PageRank | References | Authors |
0.39 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongyan Zhu | 1 | 42 | 8.57 |
| Chen Wang | 2 | 1 | 0.39 |
| Wen Jiang | 3 | 1 | 0.39 |
| Chongzhao Han | 4 | 446 | 71.68 |
| Yan Lin | 5 | 7 | 1.36 |