More Reliable Doppler Lidar for Autonomous Navigation
Sensors
More Reliable Doppler Lidar for Autonomous Navigation (LAR-TOPS-351)
Integrated sensor and algorithm provide reliable 3D imaging with velocity acquisition by salvaging compromised lidar signal data
Overview
NASA pioneered Navigation Doppler Lidar (NDL) for precision navigation and executing well-controlled landings on surfaces like the moon. This advanced lidar system utilizes Frequency Modulated Continuous Wave (FMCW) technique with homodyne detection to simultaneously determine distance to targets and velocity between the sensor and target. However, homodyne detection cannot provide phase information needed to determine the sign (+/-) of signal frequencies, resulting in false measurements of range and velocity. NASA has developed an operational prototype (TRL 6) that integrates non-mechanical beam steering with a novel algorithm to solve this critical problem. Using a three-section waveform and non-mechanical liquid crystal beam steering, the system scans the laser beam to generate 3D images while an ambiguity mitigation algorithm analyzes historical phase information to resolve frequency sign ambiguities and recover valuable measurement information from compromised signals. This complete solution enables reliable velocity and range imaging for autonomous navigation in space, air, and ground applications.
The Technology
The NDL system combines hardware innovations with advanced signal processing to deliver robust 3D velocity imaging. The sensor employs an eye-safe 1.55 micron laser with FMCW modulation, using homodyne detection to obtain changes in signal frequency caused by targets of interest. The system incorporates programmable multi-layered liquid crystal film for non-mechanical beam steering, eliminating expensive motors and encoders while mitigating vehicle vibration effects on laser beam pointing
The core innovation addresses a fundamental challenge: homodyne detection measures only absolute values of frequencies, requiring additional information to determine positive or negative signs. The three-segmented waveform - consisting of linear up-chirp, down-chirp, and constant frequency sections - allows for resolving frequency sign ambiguity. Frequency associated with each segment is positive or negative depending on relative range and direction of motion between the NDL and target.
In practical systems, one or more of the three frequencies may not be available during measurement due to target characteristics or environmental conditions. For these cases, the ambiguity mitigation algorithm uses knowledge of relative positions of frequency sideband components to predict direction of Doppler shift and sign, enabling correct range and velocity measurements. The algorithm applies an estimation filter to past measurements to provide estimates of expected new range and velocity, reducing uncertainty when signals are re-established. These estimates are used only to resolve ambiguities, never to replace actual measurements, ensuring data integrity while maximizing reliability. The sensor and algorithm are currently available for patent licensing.
Benefits
- Comprehensive Velocity Imaging: Provides both 3D range and Doppler images of surroundings, addressing the critical limitation of conventional scanning lidars that provide only static range data.
- Increased Data Reliability: Reduces ambiguities due to partial loss of signal by recovering valuable information from compromised data, improving measurement continuity and accuracy.
- Robust Mechanical Design: Non-mechanical liquid crystal beam steering eliminates moving parts, reducing maintenance requirements and mitigating effects of vehicle vibration on sensor performance.
- Easy Implementation: Algorithm works seamlessly with current homodyne sensors, enabling straightforward integration into existing FMCW lidar architectures.
- Improved Safety and Efficiency: Reduces the chance of navigation errors due to misread signals, critical for autonomous operation in safety-critical applications.
- Compact and Cost-Effective: Integrated design suitable for vehicle mounting without bulky scanning mechanisms, enabling practical deployment across multiple platforms.
Applications
- Self-Driving Cars: Provides both 3D range and Doppler images of surroundings, including speed and direction of other vehicles and pedestrians.
- Aircraft Navigation: System allows navigation in GPS-denied environments by providing velocity and altitude measurements independent of satellite signals, addressing intentional or unintentional GPS interference.
- General Automated Rendezvous and Docking: Provides relative position, approach velocity, and relative orientation and attitude of the docking port.
- Space Exploration: NDL can enable precision navigation to the desired landing location for future large robotic and crewed landing missions.
- Enables autonomous mobile robots and drones to safely navigate dynamic environments by providing real-time 3D velocity mapping of moving obstacles and terrain features.
Technology Details
Sensors
LAR-TOPS-351
LAR-19687-1
LAR-19148-1
Amzajerdian, Pierrottet, et. al. Navigation Doppler Lidar Performance at High Speed and Long Range. 2020 AIAA SciTech Forum. April 2020.
Farzin Amzajerdian, Glenn D. Hines, et al. Characterization of a Coherent Doppler Lidar for Operation Onboard Aerial and Space Vehicles. OSA Laser Congress September 29 - October 2019.
Farzin Amzajerdian, Glenn D. Hines, et al. Demonstration of coherent Doppler lidar for navigation in GPS-denied environments Proc. SPIE 10191, Laser Radar Technology and Applications XXII, May 2017.
Farzin Amzajerdian, Glenn D. Hines, et al. Characterization of a Coherent Doppler Lidar for Operation Onboard Aerial and Space Vehicles. OSA Laser Congress September 29 - October 2019.
Farzin Amzajerdian, Glenn D. Hines, et al. Demonstration of coherent Doppler lidar for navigation in GPS-denied environments Proc. SPIE 10191, Laser Radar Technology and Applications XXII, May 2017.
Similar Results
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Laser Linear Frequency Modulation System
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LiDAR with Reduced-Length Linear Detector Array
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