Ladar Data Upsampling via Interpolation

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Solution Overview

Problem

LADAR data is difficult to interpret due to its granular nature, leading to a need for improved techniques that enhance interpretability.

Innovation Solution

A system and method for upsampling LADAR data by interpolating between existing data points to create a denser point cloud, using processors to select data points within a threshold distance and height, and generating additional points through linear interpolation, resulting in an upscaled merged LADAR-edge point cloud.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If LADAR measurements are made to create three-dimensional maps, then distance and position data are obtained, but the data becomes difficult to interpret due to granular nature

Engineering Contradiction:

Improvedistance and position measurementVSAvoidinterpretability of data

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent combines multiple LADAR measurements into a merged point cloud dataset, integrating data from multiple scan lines and angles to create a comprehensive three-dimensional representation that reduces granularity and improves interpretability

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent creates interpolated data points that replicate and fill gaps in the original LADAR measurements, generating additional point cloud data through mathematical interpolation between existing measurement points to smooth the granular appearance

Inventive Principle:

Principle #26Copying

2Quantity of substance

If more LADAR measurements are made to improve data density, then measurement coverage increases, but processing complexity and time increase

Engineering Contradiction:

Improvedata densityVSAvoidprocessing time

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The patent performs preliminary interpolation operations during the data processing stage rather than requiring additional field measurements, pre-calculating intermediate point cloud data through mathematical algorithms to achieve higher density without proportional increases in processing time

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent changes the spatial distribution parameter of the point cloud by applying interpolation algorithms that generate additional points between existing measurements, effectively increasing data density through parameter transformation rather than raw data collection

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10444362B2LADAR data upsampling

Publication Date: 2019.10.15 RAYTHEON CO

AI summary

Systems and processes for increasing the effective sampling density of a LADAR data set are disclosed. LADAR data points are merged with data regarding edges of objects within the physical space represented by the LADAR data points to form a merged LADAR-edge point cloud. Each data point within the merged LADAR-edge point cloud is examined to identify co-planar neighboring data points within a defined search area. Additional data points are added to the LADAR-edge point cloud by interpolating between the identified, co-planar neighboring data points.