LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Subaperture Keystone Transform Matched Filtering Algorithm and Its Application for Air Moving Target Detection in an SBEWR System

Photo by mattpalmer from unsplash

Long-time coherent integration is an effective approach to improve detection performance for weak air moving targets (AMTs). The range position variation and azimuth Doppler variation will easily exceed range gate… Click to show full abstract

Long-time coherent integration is an effective approach to improve detection performance for weak air moving targets (AMTs). The range position variation and azimuth Doppler variation will easily exceed range gate and Doppler resolution in a long observation time, resulting in severe performance degradation, especially for high maneuverability target. Besides, the high detection performance and low computational complexity ability are, most of times, the contradiction requirements by using the existing long-time coherent integration algorithms. To overcome above constraints, a novel subaperture keystone transform matched filtering (SAKTMF) method is developed in this article based on the conventional hybrid integration (HI) algorithm, which can realize coherent integration both within the subaperture and among subapertures, effectively improving the detection performance of a weak moving target. Furthermore, the proposed SAKTMF is applied for weak AMT detection in spaceborne early warning radar, which considers serious extended clutter, range migration, and Doppler migration problems simultaneously. Simulation experiments processing results show that the proposed method can provide improved detection performance compared with the conventional HI methods.

Keywords: subaperture; performance; air moving; detection; target; detection performance

Journal Title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year Published: 2023

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.