Hybrid Time-of-Arrival Ranging for Multipath-Robust Distance Estimation
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Solution Overview
Problem
Existing time-of-arrival-based ranging methods face inaccuracies due to multipath fading and hardware-dependent amplitude variations, leading to unreliable distance measurements.
Innovation Solution
A hybrid method that combines sample-based, phase-based, and phase-amplitude-based time-of-arrival estimates, utilizing a multiple signal classification algorithm to characterize multipath components and calculate a weighted hybrid estimate, mitigating inaccuracies without increasing sampling rate or bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional time-of-arrival-based ranging methods are used, then the ranging process is simple, but the measurement precision deteriorates due to multipath fading and hardware-dependent amplitude variations
Solution Approach 1:
The patent combines three different time-of-arrival estimation methods (sample-based, phase-based, and phase-amplitude-based) into a hybrid estimation approach. Each method has different strengths and weaknesses, and by merging them with appropriate weighting, the system achieves superior ranging accuracy that overcomes the limitations of individual methods, particularly regarding multipath fading and hardware variations.
Solution Approach 2:
The patent dynamically adjusts the weighting parameters of different estimation methods based on signal conditions. By changing the weight assigned to each estimation technique according to the characteristics of the received signal and channel conditions, the system optimizes measurement precision while adapting to varying environmental factors such as multipath interference.
2Measurement precision
If sampling rate or bandwidth is increased to improve accuracy, then measurement precision improves, but energy consumption and device complexity increase
Solution Approach 1:
Instead of increasing sampling rate or bandwidth, the patent achieves improved accuracy by changing the processing approach - combining multiple estimation methods with optimized weighting. This parameter change in the estimation strategy delivers enhanced measurement precision without the energy penalty associated with higher sampling rates or bandwidth requirements.
Solution Approach 2:
The patent replaces the traditional approach of improving accuracy through physical parameters (higher sampling rate, wider bandwidth) with a signal processing substitution. By using a hybrid estimation algorithm that intelligently combines multiple methods, the system achieves equivalent or superior accuracy without the energy consumption and hardware complexity of increasing physical system parameters.
Data Source
AI summary
A method includes: receiving a ranging signal from the transmitter including a set of multiplexed sub-signals, each multiplexed sub-signal characterized by a frequency in a set of frequencies; calculating a sample-based time-of-arrival estimate based on the series of time-domain samples of the ranging signal; calculating a sample-based uncertainty of the sample-based time-of-arrival; for each sub-signal pair in a subset of multiplexed sub-signals of the set of multiplexed sub-signals, extracting a phase difference of the sub-signal pair; calculating a phase-based time-of-arrival estimate based on the phase difference of each sub-signal pair in the subset of multiplexed sub-signals; calculating a phase-based uncertainty of the phase-based time-of-arrival estimate; and calculating a hybrid time-of-arrival estimate as a weighted combination of the sample-based time-of-arrival estimate, the phase-based time-of-arrival estimate, based on the sample-based uncertainty and the phase-based uncertainty.