An Improved Total Least Squares-Based Monopulse Ratio Estimate Given Multiple Data-Snapshots from a Uniform Line Array
We derive the Total Least Squares estimate of the monopulse ratio in noise and show its superiority over the Least Squares estimate that has been studied thus far in the literature. Such superiority occurs because the Total Least Squares estimate does not exhibit the bias introduced by noise in the Least Squares case. Regarding implementation, the Total Least Squares estimate involves a simple closed-form expression of the Σ and Δ beams.
Authors
- Kai‐Bor Yu (ORCID: https://orcid.org/0000-0002-8410-1823)
- Manuel J. Fernández Iglesias (ORCID: https://orcid.org/0000-0003-4462-8724)
Publication Details
- Published
- 2024-10-21
- DOI
- https://doi.org/10.1109/radar58436.2024.10993999
- Citations
- 1
- Primary Topic
- Advanced Adaptive Filtering Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.37