Sparse MIMO Phased Array Radar for High-Resolution Imaging
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Solution Overview
Problem
Current imaging radar systems for automotive applications face challenges in balancing high resolution, long range, fast update rates, low hardware complexity, size, low power consumption, and cost, particularly in detecting small RCS targets like pedestrians, where increased angular resolution requires larger apertures leading to increased complexity, cost, and power consumption.
Innovation Solution
The implementation of Sparse MIMO Phased Array (SMPA) radar technology using subarray antenna arrays and advanced signal processing algorithms, such as Compressive Sensing and Iterative Adaptive Algorithm, to achieve high 2-D angular resolution and accuracy with reduced hardware and processing complexity, enabling real-time object detection and expanded field of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the aperture size is increased to improve angular resolution, then the angular resolution is improved, but the hardware complexity, cost, and power consumption increase
Solution Approach 1:
The radar system divides the aperture into multiple subapertures, each with its own transmit antenna and receive antenna elements. This segmentation allows the system to achieve high angular resolution through virtual aperture synthesis without requiring a single large physical aperture, thereby reducing hardware complexity while maintaining measurement precision.
Solution Approach 2:
The system transitions from a two-dimensional physical aperture to a four-dimensional virtual aperture by introducing time and frequency dimensions through MIMO techniques. Multiple transmit antennas send different waveforms, and the receive antennas capture signals at different times, creating a virtual aperture that is larger than any single physical aperture, thus improving angular resolution without proportionally increasing hardware complexity.
2Productivity
If multiple transmit antennas radiate power over a wide FoV to improve update rates, then the update rate is improved, but the detection range of small RCS targets is limited
Solution Approach 1:
The system dynamically controls the beam direction and width of each transmit antenna using phase shifters and signal processing. Instead of radiating power uniformly over a wide FoV, the system dynamically focuses energy into narrow pencil beams that can be steered across the FoV, thereby maintaining high update rates while extending detection range through concentrated energy transmission.
Solution Approach 2:
The system employs periodic beam sweeping across the field of view, where each transmit antenna sequentially directs narrow beams across different angular sectors. This periodic action allows the system to maintain high average update rates while ensuring that sufficient energy is concentrated in each beam direction to detect small RCS targets at long ranges.
3Measurement precision
If phased arrays focus energy into pencil beams to achieve long range, then the detection range is improved, but the ability to cover the desired field of view in reasonable time is limited
Solution Approach 1:
The system segments the field of view into multiple angular sectors and assigns different transmit antennas to cover different sectors simultaneously. Each antenna maintains a narrow pencil beam for long-range detection, while the collective action of multiple antennas covers the entire FoV in parallel, thereby reducing the time required to scan the complete field of view while maintaining long detection range.
Solution Approach 2:
The system adds the time dimension to the spatial distribution of beams by using sequential beam forming with phase control. Multiple narrow beams are formed at different times and angles, and through coherent integration and signal processing, the system achieves comprehensive FoV coverage without requiring each individual beam to sweep across the entire field, thus reducing total scan time while maintaining long-range detection capability.
Data Source
AI summary
High-performance 4-D Sparse MEMO Phased Array imaging and object detection radars with substantially reduced hardware and processing specifications are presented for automotive, ariel, and other application spaces. The radar antennas have 2-D angular sparse array and MIMO (Multiple Input and Multiple Output) features that can be implemented with a variety of subarrays or Antenna in Packages (AiPs) greatly simplifying the system manufacturing and feasibility. The significantly reduced data processing requirements also become feasible with the sparse subarray architectures. Advanced signal processing algorithms are presented, when coupled with the sparse and MIMO features, allow improved 2-D angular resolution of objects, improved imaging, and low sidelobes allowing the resolution of weaker targets in the presence of stronger target reflections.