Comparative Performance Analysis of Direction Finding Techniques with PCA and Variant Algorithms
13th International Conference on Electrical and Electronics Engineering, ICEEE 2026, Antalya, Türkiye, 27 - 29 Nisan 2026, ss.343-348, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/iceee69936.2026.11598308
- Basıldığı Şehir: Antalya
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.343-348
- Anahtar Kelimeler: Direction of arrival algorithms, PCA, radar, signal processing
- Gazi Üniversitesi Adresli: Evet
Özet
This paper investigates the application of Principal Component Analysis (PCA) and its variants to Direction-ofArrival (DOA) estimation in signal processing. The core objectives are threefold: to explore how PCA principles can be leveraged for direction-finding, to comparatively evaluate the performance of different PCA variants under challenging conditions (high noise, multiple sources), and to propose a novel optimized PCA-based algorithm. Simulation experiments conducted in MATLAB benchmark the PCA variants against each other in terms of estimation accuracy, computational complexity, processing speed, and noise robustness. The study also positions these methods against conventional DOA techniques - namely MUSIC and ESPRIT - analyzing the trade-offs in performance, flexibility, and hardware requirements.DOA estimation is a foundational capability across radar systems, autonomous vehicles, acoustic localization, and wireless communications. While classical methods like MUSIC and ESPRIT deliver strong performance, they are computationally intensive and sensitive to array geometry. PCA-based approaches, by contrast, are more amenable to low-cost hardware and support flexible array configurations. By systematically evaluating performance across varying noise levels, source counts, and antenna geometries, this work ultimately aims to develop a PCAbased DOA estimation algorithm suitable for deployment in realtime, resource-constrained systems.