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Remote Sensing

Description: Aerial Photo _Visible 1 (1 of 1)Description: Aerial Photo _IR 1 (1 of 1)

A low-cost aerial platform presents a flexible tool for acquiring high-resolution images for ground areas of interest. The geo-referencing of objects within these images could benefit many different research areas.  One of the FCSL Phastball aircraft was customized for remote sensing purposes. Main components of the remote-sensing payload system include a high-resolution digital still camera, a 50 Hz GPS receiver, a low-cost Inertial Navigation System (INS), a down-looking laser range finder, a custom-designed flight data recorder, and a wireless video transmission system. An extensive time-calibration and analysis effort for major measurement instruments was performed to assure that flight data were properly time-aligned. Additionally, an Unscented Kalman Filter (UKF) based 15-state GPS/INS sensor fusion algorithm was developed to estimate the aircraft attitude angles in flight. Based on the added range and orientation information for the camera, the geo-referencing software developed in Phase I effort was enhanced and its performance was evaluated using a set of flight data and the known location of a fixed reference point on the ground. The flight data analysis shows that estimates from a single aerial image resulted in approximately 7.2 m mean position error after considering lens distortion and the camera orientation corrections. Furthermore, a 0.5 m position estimation error was achieved with the averaging of 15 individual estimates.

Additional remote sensing research effort at FCSL include air-data sampling. One of the primary missions that the “SharpShooter” was designed for is aerial sampling, wherein ambient air samples could be collected by means of wing tip mounted inlets or scoops. These samples could be analyzed online using on-board sensors for near real-time characterization. Concurrently, a sample storage mechanism has been designed that is capable of storing GPS and time tagged samples in Tedlar bags. This provides the researcher the additional capability to conduct a more detailed offline analysis of the samples from various points over the area of interest. The setup is conceptually represented below and shows the proposed sample collection system and consists of a sample inlets, Tedlar storage bags and container, and pump. The pump pulls a vacuum on the container, causing the bag to expand and draw a sample, avoiding any contamination issues the pump may have on the sample.

 The primary goal is to generate 2-D and 3-D concentration profiles of a pollutant, with data from aerial sampling, using UAVs. To achieve this, the UAV will be flown at different altitudes, in a serpentine path at different altitudes over the area of interest and samples collected using inlets and scoops on the UAV. Concurrently, using an appropriate onboard sensor suite, the samples could be analyzed to generate “real-time”, geo-referenced pollutant concentrations at each sampling region. Using this data, and Kriging techniques, 2 dimensional concentration contours could be generated at a given altitude plane. Using multiple 2-D contours from different altitudes, a 3-D contour will be generated. Representative 2-D and 3-D maps with artificially generated data are shown above in Figures 4 and 5 respectively In addition to the “real time” measurements, air samples will be collected and stored onboard in Tedlar bags, for offline analysis.

Recent Publications

Gu, Y., “Evaluation of Remote Sending Aerial Systems In Existing Transportation Practices,” Project Report, WVDOH, Mid-Atlantic Universities Transportation Center (MAUTC), October 2009.