Adaptive Antenna Switching for Angle of Arrival Accuracy
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Solution Overview
Problem
Existing direction finding algorithms, such as AoX algorithms, face accuracy issues due to settling delays in antenna switching patterns caused by inductive or capacitive elements, which affect the quality of I and Q signals used for calculating angle of arrival and departure.
Innovation Solution
The system optimizes antenna switching patterns by calculating an estimated angle of arrival, sorting antenna elements based on signal parameters, and selecting a preferred switching pattern to minimize settling delays and improve signal accuracy, potentially using neural networks for pattern selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional antenna switching pattern is used, then the signal acquisition process is simple and fast, but the settling delays caused by inductive or capacitive elements reduce the quality of I and Q signals
Solution Approach 1:
The patent applies dynamics by making the antenna switching pattern adaptive rather than static. The system dynamically adjusts the switching pattern based on signal characteristics, selecting different patterns (e.g., sequential switching vs. parallel switching) depending on whether signals are strong or weak, thereby optimizing both signal quality and acquisition time under different conditions
Solution Approach 2:
The patent changes the switching pattern parameters (timing, sequence, parallel/sequential mode) based on signal strength and quality metrics. By modifying these parameters adaptively, the system minimizes settling delays while maintaining high signal quality, resolving the contradiction between measurement precision and time loss
2Measurement precision
If the acquisition time is extended to allow settling delays, then signal quality improves, but the time required to acquire signals from all antenna elements increases
Solution Approach 1:
The system dynamically adjusts the acquisition process by using multiple switching patterns with different time characteristics. For strong signals, faster patterns are used; for weak signals, patterns with longer settling times are selected, thereby maintaining productivity while ensuring sufficient signal quality
Solution Approach 2:
The patent performs preliminary signal assessment to determine signal strength and quality before selecting the appropriate switching pattern. This preliminary action allows the system to pre-select the optimal pattern that balances acquisition speed and signal quality, avoiding unnecessary delays
3Measurement precision
If multiple antenna switching patterns are implemented and selected based on signal characteristics, then measurement accuracy improves, but device complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors signal strength and quality metrics, then uses this feedback to select the appropriate switching pattern. This feedback loop automates the complexity of managing multiple patterns, making the system adaptable without requiring complex manual configuration
Solution Approach 2:
The system performs self-assessment of signal characteristics and automatically selects the optimal switching pattern without external intervention. This self-service capability handles the complexity internally, maintaining high measurement precision while keeping the user interface simple
Data Source
AI summary
A device and method for improving the accuracy of angle of arrival and departure computations is disclosed. The device and method rely on manipulation of the antenna switching pattern to achieve an improved calculation of arrival angle. In one embodiment, the device calculates an estimate angle of arrival using conventional methods. The device then determines which of a plurality of different antenna switching pattern yields the more accurate results at this estimated angle of arrival. The AoA measurement is then repeated using the preferred antenna switching pattern. In another embodiment, the device captures the amplitude and/or phase of the signal from each antenna element. The device then sorts these antenna elements and defines a preferred antenna switching pattern based on the sort list. The AoA measurement is then performed using the preferred antenna switching pattern. In another embodiment, neural networks may be utilized to determine the preferred antenna switching pattern.