Adaptive Antenna Switching Patterns for Accurate Angle of Arrival
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Solution Overview
Problem
Existing direction finding algorithms, such as AoX algorithms, face inaccuracies due to settling delays in antenna switching patterns caused by inductive or capacitive elements, which hinder the timely acquisition of accurate I and Q signals, affecting the calculation of angle of arrival and departure.
Innovation Solution
The system optimizes antenna switching patterns by calculating an estimated angle of arrival using conventional methods, sorting antenna elements based on signal amplitude or phase, and selecting a preferred switching pattern to minimize absolute error, potentially utilizing a neural network for pattern selection, ensuring accurate signal sampling and improved angle calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional antenna switching patterns are used, then the system can acquire signals from all antenna elements, but settling delays occur due to inductive or capacitive elements affecting signal accuracy
Solution Approach 1:
The patent applies dynamics by making the antenna switching pattern adaptive rather than fixed. The system dynamically selects switching patterns based on estimated angle of arrival to minimize settling delays while maintaining signal accuracy. This resolves the contradiction by allowing the system to adjust its operation in real-time based on signal characteristics.
Solution Approach 2:
The patent changes the switching pattern parameters (which antenna elements are switched and in what order) based on the estimated angle of arrival. By modifying these parameters adaptively, the system optimizes the balance between acquisition speed and measurement precision for different signal directions.
2Productivity
If antenna switching is performed to acquire signals from all elements, then direction finding can be performed, but settling delays reduce the quality of I and Q signals
Solution Approach 1:
The system performs preliminary angle estimation using initial signal acquisition, then uses this information to select an optimized switching pattern for more accurate measurements. This preliminary action allows subsequent measurements to be taken faster and more accurately by avoiding unnecessary settling periods.
Solution Approach 2:
The patent replaces the traditional mechanical-like sequential switching approach with an intelligent selection system that chooses from multiple pre-defined switching patterns. This substitution allows the system to jump to optimal configurations rather than sequentially switching through all elements, improving both speed and precision.
3Measurement precision
If multiple antenna switching patterns are evaluated, then more accurate angle of arrival can be achieved, but system complexity increases
Solution Approach 1:
Instead of evaluating all possible switching patterns, the system selectively applies a subset of patterns based on the estimated angle of arrival. This partial action approach achieves high accuracy without the computational burden of examining every possible pattern, thus managing complexity while maintaining precision.
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.