Radar Beam Steering With Dynamic Field-of-Regard Control
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Solution Overview
Problem
Radar systems face challenges in achieving high-resolution measurements while adhering to constraints of cost, size, weight, and power (C-SWAP) due to resource limitations, particularly in autonomous vehicles where high performance is needed for effective navigation.
Innovation Solution
A radar system that dynamically allocates resources by intelligently morphing its data cube and reconfiguring gain-patterns, transmit signals, and processing parameters in response to feedback inputs, allowing it to prioritize and distribute resources efficiently across the measurement space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar systems use large bandwidth receiver channels to maximize time-bandwidth-product for high-resolution measurements, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The radar system dynamically reconfigures its receiver channels and beamforming parameters in real-time based on environmental conditions and measurement requirements. The system can adaptively adjust the number of active receiver channels, bandwidth allocation, and beamforming weights to optimize measurement precision for specific scenarios while reducing complexity when full precision is not required.
Solution Approach 2:
The system changes operational parameters such as bandwidth, number of active channels, and time-bandwidth-product dynamically based on the measurement task requirements. By adjusting these parameters, the radar can achieve high measurement precision when needed while operating in a lower-complexity mode during normal conditions, effectively resolving the contradiction between precision and complexity.
2Measurement precision
If radar systems increase the number of receiver channels to improve measurement capabilities, then measurement precision is improved, but size, weight, and power consumption increase
Solution Approach 1:
The radar system employs dynamic channel activation where only the necessary number of receiver channels are activated based on current measurement requirements. This allows the system to achieve high measurement precision when full channel utilization is needed while minimizing weight and power consumption during operations that require fewer channels, effectively managing the trade-off between precision and physical constraints.
3Measurement precision
If radar systems allocate more resources to achieve high measurement resolution, then measurement precision is improved, but productivity decreases due to increased processing requirements
Solution Approach 1:
The radar system applies partial action by allocating measurement resources selectively to specific angular regions rather than uniformly across the entire field of view. Using focused beams and adaptive resource allocation, the system achieves high measurement precision in regions of interest while using fewer resources in less critical areas, thereby maintaining productivity while improving precision where needed.
Solution Approach 2:
The system implements local quality enhancement by concentrating measurement resources and processing power on specific angular regions where high precision is required, rather than uniformly distributing resources across all regions. This allows the radar to achieve high measurement precision in critical areas while maintaining overall system productivity.
Data Source
AI summary
An embodiment of a radar subsystem includes at least one antenna and a control circuit. The at least one antenna is configured to radiate at least one first transmit beam and to form at least one first receive beam. And the control circuit is configured to steer the at least one first transmit beam and the at least one first receive beam over a first field of regard during a first time period, and to steer the at least one first transmit beam and the at least one first receive beam over a second field of regard during a second time period.