LIDAR Target Identification Using Separation Distance Matching
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Solution Overview
Problem
Current LADAR systems for space operations, such as docking and landing, face inefficiencies due to the need for iterative processes in target identification, which are time-consuming and uncertain, and often require multiple sensors increasing mass, power consumption, and complexity.
Innovation Solution
A non-iterative method for identifying imaged targets using imaging LADAR systems by extracting geometric or signal-level features, sorting separation distances, and comparing them to pre-defined model data to determine pose solutions, including relative position, velocity, and attitude, through a matching algorithm and six degree of freedom least squares fitting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative algorithms (RANSAC, NFIR) are used for target identification, then measurement precision can be improved, but identification time increases significantly and uncertainty remains
Solution Approach 1:
The patent pre-calculates and stores separation distances between all pairs of points for each target model in a database before actual identification. This preliminary preparation allows the system to directly compare measured separation distances with pre-stored values during identification, eliminating the need for iterative computation and achieving instant target identification with high precision.
2Reliability
If multiple LADAR sensors are used for landing operations, then measurement reliability is improved, but system mass and power consumption increase
Solution Approach 1:
The patent makes a single flash LADAR sensor perform multiple functions that previously required separate sensors. The same sensor used for terrain mapping and hazard detection is also used for precise ranging and target identification by applying the non-iterative separation distance comparison algorithm, eliminating the need for additional LADAR sensors while maintaining comprehensive landing capabilities.
Solution Approach 2:
The patent combines multiple sensor functions into a single LADAR system. By integrating target identification, ranging, and terrain mapping capabilities into one sensor platform with a unified non-iterative processing algorithm, the system achieves the reliability of multiple sensors without their combined mass and power requirements.
3Loss of information
If multiple sensors are deployed for docking operations, then navigation data completeness is improved, but device complexity increases
Solution Approach 1:
The patent enables a single flash LADAR to provide all necessary navigation data for docking operations through its non-iterative target identification algorithm. The system extracts geometric features, calculates separation distances, and determines pose solutions using one sensor, thereby achieving complete navigation data without the complexity of coordinating multiple specialized sensors.
4Measurement precision
If scanning LADAR sensors are used for docking, then measurement capability is improved, but mass and power requirements increase
Solution Approach 1:
The patent changes the operational parameters and processing methodology from iterative scanning LADAR approaches to a non-iterative flash LADAR approach. By using flash LADAR's instantaneous wide-area illumination capability combined with pre-calculated separation distance databases, the system achieves docking measurement precision without the mass and power penalties of scanning mechanisms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables direct and efficient target identification with reduced uncertainty and complexity, allowing for precise navigation and control during docking or landing procedures without the need for multiple sensors, thereby improving operational efficiency and reliability.
Implementation Method 1
LADAR systems have also been recognized as being useful in various landing and/or docking scenarios. For example, the use of LADAR systems for docking spacecraft has been proposed.
Data Source
AI summary
The present invention pertains to the identification of a set of measurement data, using an a priori model database, which is then used in the determination of a pose solution using LADAR data. In particular, a model database of a target scene is created. The model database includes location information for a plurality of points within the target scene, and separation distances between sets of those points defining triangles. LADAR data obtained from a target scene is processed to extract features. Location information and separation distances between sets of extracted features defining triangles are placed in a measurement database. Separation distances contained in the measurement database are compared to separation distances contained in the model database. If a match is found, a rotation quaternion and translation vector are calculated, to transform the data in the measurement database into the frame of reference of the data in the model database. The rotation quaternion and translation vector can be applied to additional sets of data defining additional triangles, to verify that the target scene has been correctly identified. A pose solution and range can then be output.