Current high - performance LIDAR systems are bulky, high power to operate, and expensive. Miniaturization of these LIDAR systems is one of the very important strategies of NASA. For long-range satellite based remote sensing high performance LIDAR receiver modules are needed since the signal level is very weak and single photon sensitivity is needed for these applications. Currently, liquid nitrogen cooled LIDAR receivers are planned for these missions and miniaturization of LADAR receiver modules is not critical for these applications. However, LIDAR instruments need to be miniaturized for CubeSats, smallSats, and UAV platforms where power budget and volume are limited. Furthermore, CubeSats are low-cost mission platforms and low-cost LIDAR systems are necessary.
The major objective of this proposal is to design and demonstrate a low cost and SWAP high performance LIDAR receiver operating in the SWIR bands for CubeSats, SmallSats, and UAV platforms. We propose to demonstrate a high sensitivity, GHz bandwidth TE-cooled LIDAR receiver operating at 1.5 µm and at 2 µm wavelengths using low-noise digital alloy AlInAsSb avalanche photodiode detectors.
In Phase I we propose to demonstrate the technical feasibility of a 2-µm wavelength AlInAsSb digital alloy APD and its receiver up to 5 GHz. In Phase II, we will design and demonstrate an array LIDAR receiver with the NEP < 50 fw/rHz at GHz bandwidth at TE-cooled temperatures.
High Sensitivity low cost and SWAP LIDAR receivers will have the following NASA applications, topology and terrain mapping, surface compositional mapping, atmospheric studies, and trace gases detection, exploration of planets surfaces and characterization, and landing navigation and hazard avoidance, sense and avoidance for UAVs and future autonomous urban mobility aircraft and UAV based target imaging.
High Sensitivity LIDAR Receivers will serve DOD applications such as target identification, 3D imaging of objects in space, military autonomous vehicles navigation, and commercial applications include UAV LIDAR mapping, and autonomous navigation.