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AoA estimation

description11 papers
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lightbulbAbout this topic
Angle of Arrival (AoA) estimation is a signal processing technique used to determine the direction from which a received signal is transmitted. It is commonly applied in wireless communication systems, radar, and navigation to enhance location accuracy and improve signal tracking by analyzing the phase or time differences of incoming signals.
lightbulbAbout this topic
Angle of Arrival (AoA) estimation is a signal processing technique used to determine the direction from which a received signal is transmitted. It is commonly applied in wireless communication systems, radar, and navigation to enhance location accuracy and improve signal tracking by analyzing the phase or time differences of incoming signals.

Key research themes

1. How can mutual coupling effects be estimated and mitigated for accurate AoA estimation in antenna arrays?

Mutual coupling between antenna elements distorts the signal reception in arrays, which degrades the accuracy of Angle-of-Arrival (AoA) estimation algorithms significantly. Recent research investigates methods to jointly estimate AoAs and coupling parameters, addressing identifiability and estimation challenges that arise when the number of coupling parameters exceeds certain limits. Understanding and mitigating these effects is critical for reliable direction finding in practical antenna systems.

Key finding: This paper demonstrates that traditional AoA estimation methods suffer identifiability issues when the number of mutual coupling parameters exceeds a certain threshold (p > N^2, where N is the number of antennas). It proposes... Read more
Key finding: Building on earlier methods, this work derives a Mean-Squared-Error (MSE) expression for the proposed AoA estimator that handles numerous mutual coupling parameters. The analysis shows the proposed estimator is asymptotically... Read more
Key finding: The study proposes an enhanced Uniform Linear Array (ULA)-based geometry that appends two elements orthogonally to the linear array to mitigate weaknesses near endfire angles—regions typically degraded by mutual coupling and... Read more

2. What new algorithmic architectures enable simple, efficient, and robust AoA estimation in low-SNR and resource-limited conditions?

Standard high-resolution AoA estimation methods such as MUSIC demand multiple radio frequency chains and heavy computation, limiting their applicability in low power or hardware-constrained scenarios. Recent work explores switched beam antenna architectures combined with cross-correlation techniques, offering low complexity and hardware-friendly solutions. These methods aim to reliably estimate AoA even at low SNR, without a priori knowledge of transmitted signals, enabling practical deployment in pervasive and scalable communication systems.

Key finding: The authors propose a novel two-phase AoA estimation scheme using a switched beam antenna array and cross-correlation with an omni-directional reference signal. The scheme requires only a single RF chain connected via phase... Read more
Key finding: Addressing cost and complexity in ultra-wideband (UWB) AoA systems, this work introduces a single-antenna AoA estimation technique where dual-antenna anchors transmit packets while single-antenna tags estimate AoA via phase... Read more

3. How can parameter estimation be optimized in time series and system identification models to improve signal parameter accuracy relevant to AoA estimation?

Accurate parameter estimation in time series, ARMA models, and adaptive control systems underpins signal processing tasks including AoA estimation. Advanced estimation algorithms address challenges like noise contamination, rounding errors, model constraints, and time-varying parameters. These methods enhance robustness and precision in estimating signal model parameters, which correspondingly improves the quality of AoA estimates derived from underlying signal models.

Key finding: This paper presents a novel ARMA estimation algorithm based on representing the AR polynomial in the space spanned by forward and backward linear predictors, enabling construction of an equivalent system with two known inputs... Read more
Key finding: Focusing on ARMA parameter estimation in noisy environments, this work develops a family of adaptive algorithms integrating prior information on signal properties and tackling nonlinearities from noise. It demonstrates... Read more
Key finding: This research compares the Gradient Method (GM) and Recursive Least Squares Method (RLSM) for parameter estimation within Model Reference Adaptive Control (MRAC) systems, which are critical for real-time system adaptation.... Read more
Key finding: Introduces a nonlinear higher-order extended state observer (NHOESO) with an analytical parameterization that balances fast state estimation and robustness against measurement noise in single-input single-output nonlinear... Read more

All papers in AoA estimation