Name
Abstract | ||
|---|---|---|
We study maximum likelihood (ML) position estimation using quantized received signal strength measurements. In order to mitigate the undesired quantization effect in the observations, the dithering technique is adopted. Various dither noise distributions are considered and the corresponding likelihood functions are derived. Simulation results show that the proposed ML estimator with dithering is able to generate a significantly reduced bias but a modestly increased mean-square-error as compared to the conventional ML estimator without dithering. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CAMSAP.2015.7383782 | 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) |
Keywords | Field | DocType |
Dithering,maximum likelihood estimation,localization,quantized received signal strength | Signal processing,Control theory,Noise shaping,Estimation theory,Dither,Maximum likelihood sequence estimation,Quantization (signal processing),Probability density function,Mathematics,Estimator | Conference |
Citations | PageRank | References |
1 | 0.36 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Di Jin | 1 | 19 | 3.07 |
| Abdelhak M. Zoubir | 2 | 1036 | 148.03 |
| Feng Yin | 3 | 127 | 14.30 |
| Carsten Fritsche | 4 | 157 | 14.72 |
| Fredrik Gustafsson | 5 | 2287 | 281.33 |