Multi-Sensor Target Location Registration via Weighted Averaging
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Solution Overview
Problem
Conventional location registration systems face inaccuracies due to measurement errors, particularly in inertial registration of targets using LIDAR and barometric altitude measurements, which are affected by factors like forward velocity and rotor downwash in rotorcraft.
Innovation Solution
A system utilizing multiple sensors, including a LIDAR sensor and an altitude sensor, to measure ranges and locations, with a processor determining weighting criteria based on reliability to calculate an estimated target location value through weighted averaging, and optionally incorporating a radar sensor for secondary altitude measurements to correct errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If barometric altitude measurements are used for target location registration, then the registration process can be completed, but measurement errors occur due to forward velocity dependence and rotor downwash effects
Solution Approach 1:
The patent combines multiple sensors (LIDAR, barometric altitude sensor, and radar altimeter) to measure target location. By merging the measurements from these different sensors and applying weighting criteria based on their respective reliability, the system achieves more accurate and reliable target location registration than any single sensor could provide alone.
Solution Approach 2:
The patent changes the parameter of measurement reliability by introducing weighting criteria that dynamically adjust the contribution of each sensor's measurement. The weighting criteria are determined based on factors such as forward velocity and rotor downwash effects, allowing the system to adaptively compensate for known error sources in barometric altitude measurements.
2Measurement precision
If multiple sensors are used to improve measurement accuracy, then target location precision improves, but system complexity increases
Solution Approach 1:
The system performs self-calibration and self-weighting by automatically determining the reliability of each sensor's measurements and assigning appropriate weights. The processor autonomously calculates weighting criteria based on the operational conditions (such as forward velocity and rotor downwash), eliminating the need for manual calibration or complex external adjustment mechanisms.
3Loss of information
If LIDAR and barometric altitude measurements are combined for target registration, then location data can be obtained, but errors propagate due to forward-velocity dependence
Solution Approach 1:
The system uses feedback from multiple independent measurement sources (LIDAR range data, barometric altitude, and radar altimeter) to correct errors in the target location registration. By continuously comparing measurements from different sensors and applying weighting criteria, the system feedback-corrects for forward-velocity dependent errors in the barometric altitude measurements, preventing error propagation.
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
This approach improves the accuracy of target location registration by reducing measurement errors and continually updating location values, enhancing the precision of terrain feature identification.
Implementation Method 1
a LIDAR sensor system for measuring a plurality of ranges from a source to a target
Implementation Method 2
a barometric altitude sensor for measuring an altitude of the source above mean sea level
Data Source
AI summary
A system for registering a target includes a first sensor, a second sensor, and a processor. The first sensor measures a plurality of ranges from a source to a target, and the second sensor obtains a plurality of location measurements of the source. The system further includes a processor configured for determining one or more weighting criteria associated with each one of the plurality of location measurements based on an estimated reliability of each one of the plurality of location measurements. The processor calculates a plurality of target location values based on the plurality of ranges measured by the first sensor and the plurality of locations measured by the second sensor and calculates an estimated target location value based on the plurality of target location values weighted according to the weighting criteria.