Multi Path Signal Parameter Estimation Using Doppler Domain Sparsity
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Solution Overview
Problem
Existing methods for estimating parameters of multi-path signals, such as angle of arrival (AoA), face challenges in achieving high precision with low calculation complexity, especially when using fewer antennas or sensors than the number of paths, leading to increased complexity or reduced estimation accuracy.
Innovation Solution
The proposed solution involves a system with pre-processing units, parameter converting units, and parameter estimating units that preprocess signals to have a sparse characteristic in the Doppler frequency and angle of arrival domain, using FFT matrices to approximate Doppler frequency movement amounts and determine optimal sampling time intervals and FFT sizes to estimate AoA with high precision and low complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If more antennas or sensors are used than the number of multi paths, then estimation precision of the parameter is improved, but device complexity is increased
Solution Approach 1:
The patent transforms the estimation problem from the time domain to the Doppler frequency domain by applying FFT transformation. This parameter change in the domain of analysis allows the system to exploit the sparsity of multi-path signals in the Doppler frequency domain, achieving high estimation precision with fewer antennas by capturing the essential characteristics of each path through their unique Doppler frequencies
Solution Approach 2:
The patent introduces a new dimension (Doppler frequency domain) to the estimation problem. By transforming the signal representation from spatial domain (antenna array) to frequency domain (Doppler spectrum), the system can resolve multiple paths using their frequency separation rather than requiring spatial separation through more antennas
2Measurement precision
If compressive sensing method is used to estimate channel, then AoA can be estimated with high precision even with less antennas, but calculation complexity is increased
Solution Approach 1:
The patent performs preliminary action by applying FFT transformation to convert the received signal into the Doppler frequency domain before parameter estimation. This pre-processing step creates a sparse representation of the multi-path signal where each path corresponds to a distinct frequency component, significantly simplifying the subsequent AoA estimation process and reducing computational complexity compared to direct compressive sensing methods
Solution Approach 2:
The patent replaces the complex iterative optimization processes typical of compressive sensing with a more efficient frequency-domain approach using FFT. This substitution of the estimation mechanism leverages the computational efficiency of Fast Fourier Transform algorithms to achieve the same sparsity exploitation goal with much lower computational burden
Data Source
AI summary
Disclosed are an apparatus and a method for estimating a parameter of a multi path signal. The apparatus for estimating a parameter of a multi path signal includes: a plurality of pre-processing units configured to pre-process respective reception signals received through a plurality of antennas; a plurality of parameter converting units configured to approximate a parameter set of the respective pre-processed reception signals to have a sparse characteristic in a Doppler frequency and angle of arrival domain; and a parameter estimating unit configured to estimate an angle of arrival for a plurality of reception signals in each frequency region of the Doppler frequency and angle of arrival domain.