The small target detection in High Frequency Surface Wave Radar is limited by the presence of various clutter and interference. Several novel signal processing techniques are developed to improve the system detection performance.
As an external interference due to local lightning, impulsive noise increases the broadband noise level and then precludes the targets from detection. A new excision approach is proposed with modified linear predictions as the reconstruction solution. The system performance is further improved by de-noising the estimated covariance matrix through signal property mapping method.
The existence of non-stationary sea clutter and ionospheric clutter can result in excessive false alarm rate through the high sidelobe level in adaptive beamforming. The optimum threshold discrete quadratic inequality constraints method is proposed to guarantee the sidelobe-controlling problem consistently feasible and optimal. This constrained optimization problem can be formulated into a second order cone problem with efficient mathematical solution. Both simulation and experimental results validate the improved performance and feasibility of our method.
Based on the special noise characteristics of High Frequency radar, an adaptive switching Constant False Alarm Rate detector is proposed for targets detection in the beamformed range-Doppler map. The switching rule and adaptive footprint are applied to provide the optimum background noise estimation. For this new method about 14% probability of detection improvement has been verified by experimental data, and meanwhile the false alarm rate is reduced significantly compared to the original CFAR.
The conventional Doppler processing has difficulty to recognize a target if its frequency is close to a Bragg line. One detector is proposed to solve this co-located co-channel resolvability problem under the assumption that target/clutter have different phase modulation. Moreover with the pre-whitening processing, the Reversible Jump Markov Chain Monte Carlo method can provide target number and Direction-of-Arrival estimation with lower detection threshold compared to beamforming and subspace methods. RJMCMC is able to convergent to the optimal resolution for a data set that is small compared with information theoretic criteria.
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/2004 |
| Date | 18 December 2009 |
| Creators | Lu, Xiaoli |
| Contributors | Kirlin, R. Lynn, Zielinski, Adam |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
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