SMAP L-Band Microwave Radiometer: Instrument Design and First Year on Orbit.

The Soil Moisture Active-Passive (SMAP) L-band microwave radiometer is a conical scanning instrument designed to measure soil moisture with 4% volumetric accuracy at 40-km spatial resolution. SMAP is NASA's first Earth Systematic Mission developed in response to its first Earth science decadal survey. Here, the design is reviewed and the results of its first year on orbit are presented. Unique features of the radiometer include a large 6-m rotating reflector, fully polarimetric radiometer receiver with internal calibration, and radio-frequency interference detection and filtering hardware. The radiometer electronics are thermally controlled to achieve good radiometric stability. Analyses of on-orbit results indicate that the electrical and thermal characteristics of the electronics and internal calibration sources are very stable and promote excellent gain stability. Radiometer NEDT < 1 K for 17-ms samples. The gain spectrum exhibits low noise at frequencies >1 MHz and 1/f noise rising at longer time scales fully captured by the internal calibration scheme. Results from sky observations and global swath imagery of all four Stokes antenna temperatures indicate that the instrument is operating as expected.

Amplitude-based height-reconstruction techniques for synthetic aperture ladar systems.

We examine the performance of amplitude-based height-estimation techniques for use with airborne synthetic aperture ladar (SAL) sensors in generating three-dimensional reconstructions of ground targets. Such techniques lend themselves to implementation more readily than phase-based techniques and are also more tolerant to phase instabilities that might be associated with SAL systems. For pairwise amplitude-comparison monopulse processing, we present analyses of the expected height sensitivity and bias of SAL systems in terms of the system parameters. We verify this analysis with simulations, and we also provide an overview of other SAL phenomena that affect height-estimation accuracy. We then propose an array-based joint-processing approach that can be applied instead of pairwise monopulse processing. We show that the joint-processing approach represents the maximum-likelihood estimator for obtaining the target height, and we demonstrate that the proposed approach significantly reduces bias-induced errors.