Towards Low Latency and Resource-Efficient FPGA Implementations of the MUSIC Algorithm for Direction of Arrival Estimation

Butt, Uzma M.; Khan, Shoab A.; Ullah, Anees; Khaliq, Abdul; Reviriego, Pedro; Zahir, Ali

doi:10.1109/tcsi.2021.3083280

Cited by 25 publications

(7 citation statements)

References 26 publications

(71 reference statements)

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“…Based on [39,40], the validation of the proposed CbSS technique can be carried out using field programmable gate array (FPGA) prototyping platforms. In past DOA estimation literature, such as [39,41], practical experiments have demonstrated that it can meet real-world applications with sufficient computational complexities of the same subspace-based class of DOA estimators. In addition, a comprehensive comparison and performance analysis against geometric-based DOA estimators can be carried out to compare the estimation robustness and accuracy.…”

Section: Discussionmentioning

confidence: 99%

A Covariance Matrix Reconstruction Approach for Single Snapshot Direction of Arrival Estimation

Muhammad

Abbasi

et al. 2022

Sensors

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Achieving accurate single snapshot direction of arrival (DOA) information significantly improves communication performance. This paper investigates an accurate and high-resolution DOA estimation technique by enabling single snapshot data collection and enhancing DOA estimation results compared to multiple snapshot methods. This is carried out by manipulating the incoming signal covariance matrix while suppressing undesired additive white Gaussian noise (AWGN) by actively updating and estimating the antenna array manifold vector. We demonstrated the estimation performance in simulation that our proposed technique supersedes the estimation performance of existing state-of-the-art techniques in various signal-to-noise ratio (SNR) scenarios and single snapshot sampling environments. Our proposed covariance-based single snapshot (CbSS) technique yields the lowest root-mean-squared error (RMSE) against the true DOA compared to root-MUSIC and the partial relaxation (PR) approach for multiple snapshots and a single signal source environment. In addition, our proposed technique presents the lowest DOA estimation performance degradation in a multiple uncorrelated and coherent signal source environment by up to 25.5% with nearly negligible bias. Lastly, our proposed CbSS technique presents the best DOA estimation results for a single snapshot and single-source scenario with an RMSE of 0.05° against the true DOA compared to root-MUSIC and the PR approach with nearly negligible bias as well. A potential application for CbSS would be in a scenario where accurate DOA estimation with a small antenna array form factor is a limitation, such as in the intelligent transportation system industry and wireless communication.

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Section: Discussionmentioning

confidence: 99%

A Covariance Matrix Reconstruction Approach for Single Snapshot Direction of Arrival Estimation

Muhammad

Abbasi

et al. 2022

Sensors

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“…The algorithm was simulated to work up to 1 GHz clock frequency, on a TMSC 40-nm CMOS technology. In [16], Butt et al implemented an optimized version of the MUSIC algorithm with reduced processing time and resource occupation using a Xilinx FPGA The improvement is obtained by normalizing the covariance matrix and reducing its size by considering only three adjacent antennas and then choosing to evaluate the best-received signal level. The estimation takes a few µs.…”

Section: Related Workmentioning

confidence: 99%

A Reconfigurable Full-Digital Architecture for Angle of Arrival Estimation

Florio¹,

Avitabile²,

Talarico³

et al. 2023

Preprint

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<p>In recent years, Real-Time Localization Systems (RTLS) are gaining significant attention from the scientific community. Usually, RLTS rely on positioning techniques based on the electromagnetic (e.m.) propagation properties of the received signals. Among the many possible approaches, RTLS based on the Angle-of-Arrival (AoA) estimation allows for accurate results with a comparatively lower number of receivers. In this work, we propose a novel, fully digital synchronous architecture for AoA estimation based on phase interferometry. After reviewing the state of-the-art on full-hardware techniques for localization, the main blocks composing the proposed architecture, are discussed in detail, along with their dimensioning equations. The granularity with which the system estimates the phase shifts used to compute the AoA is reconfigurable according to the desired accuracy. The architecture is lightweight and computes the AoA in real-time. To validate the proposed approach, the RTLS architecture has been implemented on an Intel Cyclone IV E EP4CE115F29C7 FPGA board interfaced with a custom-designed receiver front-end, and experimental results on benchmark applications have been collected and analyzed.</p>

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“…With the challenge of creating an audio-only sensor system to localize and identify speakers without requiring a video-based solution, this work presents an embedded, costeffective, low-power, and real-time microphone array solution for speaker localization and identification that can be used inside an SAV. To accelerate the processing tasks, the sensor system resorts to Field-Programmable Gate Array (FPGA) technology to deploy dedicated processing modules in hardware to interface, acquire, and compute data from different microphones [44][45][46][47][48][49]. Moreover, the processing system provides a Robot Operating System (ROS) interface to make data available to other high-level applications (for the identification and classification of audio events) or to other sensor fusion systems.…”

Section: Introductionmentioning

confidence: 99%

Microphone Array for Speaker Localization and Identification in Shared Autonomous Vehicles

et al. 2022

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With the current technological transformation in the automotive industry, autonomous vehicles are getting closer to the Society of Automative Engineers (SAE) automation level 5. This level corresponds to the full vehicle automation, where the driving system autonomously monitors and navigates the environment. With SAE-level 5, the concept of a Shared Autonomous Vehicle (SAV) will soon become a reality and mainstream. The main purpose of an SAV is to allow unrelated passengers to share an autonomous vehicle without a driver/moderator inside the shared space. However, to ensure their safety and well-being until they reach their final destination, active monitoring of all passengers is required. In this context, this article presents a microphone-based sensor system that is able to localize sound events inside an SAV. The solution is composed of a Micro-Electro-Mechanical System (MEMS) microphone array with a circular geometry connected to an embedded processing platform that resorts to Field-Programmable Gate Array (FPGA) technology to successfully process in the hardware the sound localization algorithms.

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Towards Low Latency and Resource-Efficient FPGA Implementations of the MUSIC Algorithm for Direction of Arrival Estimation

Cited by 25 publications

References 26 publications

A Covariance Matrix Reconstruction Approach for Single Snapshot Direction of Arrival Estimation

A Covariance Matrix Reconstruction Approach for Single Snapshot Direction of Arrival Estimation

A Reconfigurable Full-Digital Architecture for Angle of Arrival Estimation

Microphone Array for Speaker Localization and Identification in Shared Autonomous Vehicles

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