Title :
The performance of maximum likelihood over-the-horizon radar coordinate registration
Author :
Anderson, Richard H. ; Krolik, Jeffrey Y L
Author_Institution :
Dept. of Electr. Eng., Duke Univ., Durham, NC, USA
Abstract :
A well-known source of target localization errors in over-the-horizon radar is the uncertainty about downrange ionospheric conditions. Maximum likelihood (ML) coordinate registration, using statistical modeling of ionospheric parameters, has recently been proposed as a method which is robust to ionospheric variability. This paper reports ML performance results for real data from a known target using estimates of ionospheric statistics derived from ionosonde measurements. Bootstrap samples derived from these statistics are then used in a hidden Markov model approximation to the ground range likelihood function. Comparison of the ML and conventional methods for over 250 radar dwells indicates the new technique achieves better than a factor of two improvement in ground range accuracy
Keywords :
ionospheric electromagnetic wave propagation; maximum likelihood estimation; radar detection; radar theory; radar tracking; ray tracing; target tracking; OTH radar; bootstrap samples; downrange ionospheric conditions; ground range likelihood function; hidden Markov model approximation; ionosonde measurements; ionospheric parameters; ionospheric statistics; ionospheric variability; maximum likelihood coordinate registration; over-the-horizon radar; statistical modeling; target localization errors; Azimuth; Chromium; Frequency; Hidden Markov models; Maximum likelihood detection; Maximum likelihood estimation; Plasma measurements; Radar; Robustness; Uncertainty;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.681654