A Review of Sparsity-Based Methods for Analysing Radar Returns from Helicopter Rotor Blades
Defence Science and Technology Group Edinburgh, South Australia Australia
Pagination or Media Count:
Radar imaging of rotating blade-like objects, such as helicopter rotors, using narrowband radar has lately been of significant interest these objects cannot be adequately described by the classic point-scatterer model. Recently, a novel tilted-wire scatterer model has been developed that can provide an accurate and sparse representation of radar returns from such objects. Following a literature review on compressed sensing algorithms, covering both greedy and lp minimisation methods 0 p- 1, the report focuses on a comparative study of various greedy pursuit algorithms, using both simulated and real radar data, with a particular emphasis on the use of the tilted-wire scatterer model. It is observed that the greedy algorithms that select multiple atoms at the matched-filtering stage do not perform well when the atoms used in the dictionary are significantly correlated. Amongst the greedy algorithms, Orthogonal Matching Pursuit OMP exhibits the best performance, closely followed by Conjugate Gradient Pursuit CGP, which has a much smaller computational complexity than OMP. In applications where the tilted-wire model requires large dictionaries and large CPI atoms, CGP is the preferred option.
- Active and Passive Radar Detection and Equipment