High-Resolution Range Profile Classifiers Require Aspect-Angle Awareness

Researchers demonstrate that High-Resolution Range Profile (HRRP) classifiers achieve significantly better accuracy when incorporating aspect-angle information, showing 7% average improvement and up to 10% gains. The study proves that estimated angles via Kalman filtering can preserve most benefits, making the approach viable for real-world radar and signal processing applications.

• →HRRP classifiers with aspect-angle conditioning achieve 7% average accuracy improvement over traditional methods.
• →Both single-profile and sequential classifier architectures benefit consistently from aspect-angle awareness.
• →Causal Kalman filters can estimate aspect angles online with median error of only 5 degrees.
• →Training with estimated angles preserves most accuracy gains, supporting real-world implementation.
• →The research challenges assumptions that aspect-angle information should be unavailable during inference.