Comparison of filtering and smoothing algorithms for airborne radar data
2013
The detection of ground-moving targets requires clutter cancellation, which is typically performed using space-time
adaptive processing (STAP). The detections from STAP provide the measurements of range, bearing, and
Doppler. These measurements can then be fed to Bayesian state estimators. In this paper, results from an
airborne radar data set are processed and the performance of filtering and smoothing algorithms are compared.
The standard nonlinear filtering algorithms, namely the extended Kalman filter, are used. It is found that while
the smoother performance is significantly better than that of the filter, the smoothing window need not be large
to obtain the superior performance.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
7
References
0
Citations
NaN
KQI