Distributed Radar Antenna Arrays With Neural Virtual Antennas
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Solution Overview
Problem
Current MIMO radar systems have limited resolution in the elevation dimension due to the restriction of transmit antennas at different elevations and separate processing of azimuth and elevation data, necessitating improved elevation resolution and joint processing capabilities.
Innovation Solution
Implement a radar system with physical receive antennas at varying elevations and utilize a neural network to generate data for virtual antenna arrays, filling gaps and performing joint processing of azimuth and elevation data, thereby enhancing elevation resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current MIMO radar systems use only transmit antennas at different elevations, then the system structure is simple, but the elevation resolution is limited
Solution Approach 1:
The patent introduces receive antennas at different elevations, adding a new spatial dimension to the traditional MIMO configuration. This creates a three-dimensional antenna geometry that enables improved elevation resolution by providing additional viewing angles and spatial sampling in the vertical dimension.
Solution Approach 2:
The system creates virtual antenna arrays through signal processing that replicate the functionality of additional physical antennas. By processing signals from the distributed physical antennas, the system generates virtual receive antennas at various elevations, effectively copying the resolution-enhancing capability without requiring additional physical hardware at each location.
2Measurement precision
If current MIMO radar systems process azimuth and elevation data separately, then the processing is straightforward, but the resolution and accuracy are limited
Solution Approach 1:
The patent merges azimuth and elevation processing into a unified joint processing framework. By combining the data from multiple physical antennas at different elevations and processing them simultaneously, the system achieves improved target localization accuracy and resolves the limitations of separate processing approaches.
Solution Approach 2:
The system introduces virtual antenna arrays as an intermediary representation that bridges the physical antenna configuration and the final target detection. This virtual array serves as a mediator that transforms the raw signals from distributed physical antennas into enhanced spatial information for both azimuth and elevation dimensions.
3Measurement precision
If the spacing between virtual antennas is greater than λ/2, then the system can accommodate fewer antennas, but the resolution is reduced
Solution Approach 1:
The system uses machine learning models to generate virtual antenna data that replicates the signal characteristics of physical antennas. This allows the system to create multiple virtual antennas with appropriate spacing while maintaining resolution, as the virtual antennas are synthesized through intelligent signal processing rather than requiring physical counterparts.
Solution Approach 2:
The patent dynamically adjusts the spacing and distribution of virtual antennas based on the specific detection requirements and signal characteristics. By changing the virtual array configuration parameters adaptively, the system optimizes the balance between the number of antennas and resolution for different operational scenarios.
Data Source
AI summary
A radar system comprises a physical radar array including a plurality of physical transmit antennas, each configured to transmit a respective signal having a wavelength λ. The physical radar array further comprises a plurality of physical receive antennas, each configured to receive each of the respective transmitted signals. At least one of the plurality of physical receive antennas is positioned at a different elevation than the other receive antennas. In some embodiments at least one of the plurality of physical transmit antennas is positioned at a different elevation than the other transmit antennas. In some embodiments the radar system further comprises a neural network arranged to receive data from the physical radar array and to generate or update data for one or more missing virtual antennas, generate a new fraction of the virtual antennas, generate the full set of virtual antennas, or directly generate the processed data.