Showing 2 results for Doa
Sh. Shirvani Moghaddam, Z. Ebadi, V. Tabataba Vakili,
Volume 11, Issue 1 (3-2015)
Abstract
In this paper, a new combination of Minimum Description Length (MDL) or Eigenvalue Gradient Method (EGM), Joint Approximate Diagonalization of Eigenmatrices (JADE) and Modified Forward-Backward Linear Prediction (MFBLP) algorithms is proposed which determines the number of non-coherent source groups and estimates the Direction Of Arrivals (DOAs) of coherent signals in each group. First, the MDL/EGM algorithm determines the number of non-coherent signal groups, and then the JADE algorithm estimates the generalized steering vectors considering white/colored Gaussian noise. Finally, the MFBLP algorithm is applied to estimate DOAs of coherent signals in each group. A new Normalized Root Mean Square Error (NRMSE) is also proposed that introduces a more realistic metric to compare the performance of DOA estimation methods. Simulation results show that the proposed algorithm can resolve sources regardless of QAM modulation size. In addition, simulations in white/colored Gaussian noises show that the proposed algorithm outperforms the JADE-MUSIC algorithm in a wide range of Signal to Noise Ratios (SNRs).
Zahra Memarian, Mahdi Majidi,
Volume 21, Issue 3 (8-2025)
Abstract
This paper presents a two-dimensional (2D) direction of arrival (DOA) estimation method based on the popular correlative interferometer (CI) approach, incorporating practical considerations. Leveraging the flexibility of software-defined radio (SDR) platforms, the proposed array antenna model is designed according to the specifications of a dual-channel synchronous USRP B210 receiver and an appropriate RF switch. To enhance the speed and accuracy of 2D DOA estimation for narrowband, wideband (WB), and frequency hopping (FH) signals, this study introduces a method that integrates power spectrum density (PSD) and spectrogram analysis of the receiver’s instantaneous bandwidth with an optimized filter bank, to precisely detect active frequencies and their intervals. Additionally, a fast, modified K-means clustering algorithm is developed to refine DOA estimation for FH and WB signals across multiple active subchannels. Simulation results demonstrate improved DOA estimation accuracy in multipath conditions, particularly at longer distances, with further enhancements achieved through the proposed clustering method.
