FMCW Source Nonlinearity Compensation with Sparse Frequency Sampling
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Solution Overview
Problem
Existing FMCW-based systems face challenges in accurately estimating and compensating for non-linearity in linearly swept sources due to hardware impairments, which degrade range resolution and sensitivity, particularly at long measurement distances, and require additional hardware resources for correction.
Innovation Solution
A cost-effective FMCW-based system that uses a frequency filter, such as an etalon, to sparsely sample the modulated signal, transforming it into the frequency domain to separate linear and non-linear components, and employs a basis function approximation to estimate and compensate for non-linearity without a dedicated reference arm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dedicated reference path is used to eliminate unknown non-linearity and estimate modulation nonlinearity, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The patent extracts only the essential function of non-linearity estimation by using a frequency filter to sparsely sample the modulated signal, separating it from the complete reference path approach. This extracts the core measurement function while removing unnecessary hardware complexity
Solution Approach 2:
Instead of using a physical reference path with dedicated hardware, the patent creates a virtual reference by sparsely sampling the modulated signal through frequency filtering. This virtual copy provides the necessary non-linearity estimation data without requiring physical duplication of the measurement path
2Device complexity
If sparse sampling of the modulated signal is used to estimate non-linearity, then device complexity reduces, but measurement precision may deteriorate
Solution Approach 1:
The frequency filter acts as an intermediary that enables non-linearity estimation from sparsely sampled data. It mediates between the limited sampled points and the required accuracy by providing a structured approach to reconstruct the non-linearity characteristics
Solution Approach 2:
The patent changes the sampling parameters by using sparse sampling at specific frequency points rather than continuous sampling. This parameter change reduces hardware requirements while maintaining estimation accuracy through the frequency domain analysis and basis function approximation
3Productivity
If basis function approximation is used to estimate non-linearity coefficients, then processing speed improves, but measurement precision may be affected
Solution Approach 1:
The patent transforms the non-linearity estimation problem from the time domain to the frequency domain, changing the parameters of analysis. This transformation enables the use of basis function approximation that is computationally efficient while maintaining accuracy in representing the non-linear characteristics
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach improves range estimation accuracy and reduces system complexity and cost by effectively compensating for non-linearity in the modulated signal, maintaining high sensitivity and resolution across varying distances.
Implementation Method 1
a frequency filter operatively connected to the emitter, the frequency filter passing the linearly modulated wave transmitted by the emitter at different time instances at the predetermined frequencies to generate measurements of the modulated wave in a time-domain
Implementation Method 2
convert the measurements of the linearly modulated wave from the time-domain into a frequency-domain to produce a non-linear frequency signal
Implementation Method 3
a mixer operatively connected to the emitter and the receiver and configured to interfere a copy of the wave transmitted by the emitter with the reflection of the transmitted wave received by the receiver to generate a beat signal
Data Source
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Figure 3A
AI summary
A frequency modulation continuous wave (FMCW)-based system configured to convert measurements of a linearly modulated wave from a time-domain into a frequency-domain to produce a non-linear frequency signal, where the non-linear frequency signal comprises a known linear component representing the desired linear modulation and an unknown non-linear component representing the non-linearity of the modulation. The FMCW-based system is further configured to determine coefficients of a basis function approximating a difference between the non-linear frequency signal and the linear frequency component in the frequency domain. The FMCW-based system is further configured to detect one or multiple spectrum peaks in the distorted beat signal with the distortion compensated according to the basis function with the determined coefficients to determine one or multiple distances to the one or multiple objects in the scene.