One-Bit Antenna Array DoA Estimation Under Low-SNR Quantization Noise
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Solution Overview
Problem
Existing one-bit DoA estimation models fail to accurately describe noise distribution in low signal-to-noise ratio scenarios, leading to poor performance due to unmanaged quantization errors.
Innovation Solution
A method for DoA estimation using one-bit quantization antenna arrays that remodels the received signal model to incorporate noise distribution information, employing a proximal alternating minimization method and gradient descent to optimize the estimation process, utilizing specific norms to constrain and penalize noise characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If one-bit quantization is used to simplify the ADC system, then device complexity and energy consumption are reduced, but measurement precision deteriorates due to quantization errors
Solution Approach 1:
The patent applies this principle by transforming the harmful quantization errors into a manageable statistical model. By characterizing the noise distribution caused by one-bit quantization and incorporating it into the loss function, the system converts the degradation from quantization into a controllable factor that can be optimized through proper algorithm design, thereby recovering measurement precision while maintaining the simplicity of one-bit ADC.
Solution Approach 2:
The patent changes the parameter representation by introducing a noise distribution model that describes the statistical characteristics of quantization errors. By modeling the noise as having specific distribution properties and incorporating these parameters into the optimization framework, the system can compensate for the precision loss from one-bit quantization through parameter-based correction in the loss function.
2Device complexity
If conventional loss functions are used in one-bit DoA estimation, then algorithm simplicity is maintained, but reliability deteriorates in low signal-to-noise ratio scenarios due to inability to suppress quantization errors
Solution Approach 1:
The patent transforms the harmful effect of quantization errors in low SNR scenarios by developing a specialized loss function that incorporates noise distribution characteristics. This loss function converts the previously harmful quantization noise into a modeled component that can be suppressed through optimization, thereby improving reliability without excessive complexity increase.
Solution Approach 2:
The patent implements feedback by using the characterized noise distribution to inform the loss function design. The noise model provides feedback about the expected error characteristics, which is then incorporated into the optimization criterion to guide the estimation process, creating a closed-loop approach that improves reliability in low SNR conditions.
3Device complexity
If existing observation models are used for one-bit DoA estimation, then model simplicity is maintained, but measurement precision deteriorates because noise distribution cannot be accurately described
Solution Approach 1:
The patent applies preliminary action by pre-characterizing the noise distribution that results from one-bit quantization before performing DoA estimation. By establishing the noise model in advance and incorporating it into the loss function design, the system prepares the optimization framework with accurate noise statistics, enabling precise angle estimation despite the simplicity of the observation model.
Solution Approach 2:
The patent introduces new parameters that describe the noise distribution characteristics caused by one-bit quantization. By adding these distribution parameters to the model and incorporating them into the loss function, the system enhances measurement precision without significantly increasing observation model complexity, as the improvement comes from better parameter characterization rather than model structural complexity.
Data Source
AI summary
A method and a device for direction of arrival estimation based on one-bit quantization antenna array, the method including: designing a received signal model of robust one-bit radar, designing an optimal objective function of the robust one-bit radar, replacing a first function in the optimal objective function with a second objective function to obtain a new optimal objective function, and according to the new optimal objective function, adopting a proximal alternating minimization method and a gradient descent method to solve the optimization problem and obtain an incident angle of a target echo signal. The embodiments reshape the received signal model of the one-bit radar, enabling the received signals to preserve or reflect the distribution information of noise data. The embodiments utilize a specific norm to describe the distribution of noise, effectively suppressing quantization error bits generated by low signal-to-noise ratio when estimating DoA with one-bit algorithm.