Soil Moisture Active/Passive (SMAP) Forward Brightness Temperature Simulator

The SMAP is one of four first-tier missions recommended by the US National Research Council's Committee on Earth Science and Applications from Space (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, Space Studies Board, National Academies Press, 2007) [1]. It is to measure the global soil moisture and freeze/thaw from space. One of the spaceborne instruments is an L-band radiometer with a shared single feedhorn and parabolic mesh reflector. While the radiometer measures the emission over a footprint of interest, unwanted emissions are also received by the antenna through the antenna sidelobes from the cosmic background and other error sources such as the Sun, the Moon and the galaxy. Their effects need to be considered accurately, and the analysis of the overall performance of the radiometer requires end-to-end performance simulation from Earth emission to antenna brightness temperature, such as the global simulation of L-band brightness temperature simulation over land and sea [2]. To assist with the SMAP radiometer level 1B algorithm development, the SMAP forward brightness temperature simulator is developed by adapting the Aquarius simulator [2] with necessary modifications. This poster presents the current status of the SMAP forward brightness simulator s development including incorporating the land microwave emission model and its input datasets, and a simplified atmospheric radiative transfer model. The latest simulation results are also presented to demonstrate the ability of supporting the SMAP L1B algorithm development

Polarimetric Microwave Radiometer Calibration.

A polarimetric radiometer is a radiometer with the capability to measure the correlation information between vertically and horizontally polarized electric fields. To better understand and calibrate this type of radiometer, several research efforts have been undertaken. 1) All microwave radiometer measurements of brightness temperature (TB) include an additive noise component. The variance and correlation statistics of the additive noise component of fully polarimetric radiometer measurements are derived from theoretical considerations and the resulting relationships are verified experimentally. It is found that the noise can be correlated among polarimetric channels and that the correlation statistics can vary as a function of the polarization state of the scene under observation. 2) A polarimetric radiometer calibration algorithm has been developed which makes use of the Correlated Noise Calibration Standard (CNCS) to aid in the characterization of microwave polarimetric radiometers and to characterize the non-ideal characteristics of the CNCS itself simultaneously. CNCS has been developed by the Space Physics Research Laboratory of the University of Michigan (SPRL). The calibration algorithm has been verified using the DetMit L-band radiometer. The precision of the calibration is estimated by Monte Carlo simulations. A CNCS forward model has been developed to describe the non-ideal characteristics of the CNCS. Impedance-mismatches between the CNCS and radiometer under test are also considered in the calibration. 3) The calibration technique is demonstrated by applying it to the Engineering Model (EM) of the NASA Aquarius radiometer. CNCS is used to calibrate the Aquarius radiometer – specifically to retrieve its channel phase imbalance and the thermal emission characteristics of transmission line between its antenna and receiver. The impact of errors in calibration of the radiometer channel phase imbalance on Sea Surface Salinity (SSS) retrievals by Aquarius is also analyzed. 4) The CNCS has also been used to calibrate the Breadboard Model (BM) of the L-band NASA Juno radiometer. In order to cover the broad TB dynamic range of the Juno radiometer, a special linearization process has been developed for the CNCS. The method combines multiple Arbitrary Waveform Generator gaussian noise signals with different values of variance to construct the necessary range of TB levelsPh.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61741/1/jzhpeng_1.pd

Effects of clock frequency stability on digital microwave radiometer performance

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94800/1/rds5731.pd

Improved Calibration through SMAP RFI Change Detection

Anthropogenic Radio-Frequency Interference (RFI) drove both the SMAP (Soil Moisture Active Passive) microwave radiometer hardware and Level 1 science algorithm designs to use new technology and techniques for the first time on a spaceflight project. Care was taken to provide special features allowing the detection and removal of harmful interference in order to meet the error budget. Nonetheless, the project accepted a risk that RFI and its mitigation would exceed the 1.3-K error budget. Thus, RFI will likely remain a challenge afterwards due to its changing and uncertain nature. To address the challenge, we seek to answer the following questions: How does RFI evolve over the SMAP lifetime? What calibration error does the changing RFI environment cause? Can time series information be exploited to reduce these errors and improve calibration for all science products reliant upon SMAP radiometer data? In this talk, we address the first question

Soil Moisture Active Passive (SMAP) Project Algorithm Theoretical Basis Document SMAP L1B Radiometer Data Product: L1B_TB

The purpose of the Soil Moisture Active Passive (SMAP) radiometer calibration algorithm is to convert Level 0 (L0) radiometer digital counts data into calibrated estimates of brightness temperatures referenced to the Earth's surface within the main beam. The algorithm theory in most respects is similar to what has been developed and implemented for decades for other satellite radiometers; however, SMAP includes two key features heretofore absent from most satellite borne radiometers: radio frequency interference (RFI) detection and mitigation, and measurement of the third and fourth Stokes parameters using digital correlation. The purpose of this document is to describe the SMAP radiometer and forward model, explain the SMAP calibration algorithm, including approximations, errors, and biases, provide all necessary equations for implementing the calibration algorithm and detail the RFI detection and mitigation process. Section 2 provides a summary of algorithm objectives and driving requirements. Section 3 is a description of the instrument and Section 4 covers the forward models, upon which the algorithm is based. Section 5 gives the retrieval algorithm and theory. Section 6 describes the orbit simulator, which implements the forward model and is the key for deriving antenna pattern correction coefficients and testing the overall algorithm

Soil Moisture ActivePassive (SMAP) L-Band Microwave Radiometer Post-Launch Calibration

The SMAP microwave radiometer is a fully-polarimetric L-band radiometer flown on the SMAP satellite in a 6 AM/ 6 PM sun-synchronous orbit at 685 km altitude. Since April, 2015, the radiometer is under calibration and validation to assess the quality of the radiometer L1B data product. Calibration methods including the SMAP L1B TA2TB (from Antenna Temperature (TA) to the Earths surface Brightness Temperature (TB)) algorithm and TA forward models are outlined, and validation approaches to calibration stability/quality are described in this paper including future work. Results show that the current radiometer L1B data satisfies its requirements

Recalibration and Validation of the SMAP L-Band Radiometer

SMAP mission was launched on 31st January 2015 in a 6 AM 6 PM sun-synchronous orbit at 685 km altitude to measure soil moisture and freethaw globally. The passive instrument of SMAP is a fully polarimetric L-band radiometer (1.4GHz) operating with a bandwidth of 24MHz. The radiometer L1B data product version 3 has been released for public science activities. Post-launch calibration and validation activities are described in [4,5]. Validation results show that SMAP antenna temperature (TA) is 2.6 K warmer over galactic Cold Sky (CS), and land TB is 2.6 K colder comparing to SMOS land TB (compared at the top of the atmosphere) after the update of the reflectors thermal model. Due to the biases, the SMAP radiometer is under re-calibration for next data release in 2018.We present the updated calibration approaches for the SMAP radiometer product. We will discuss the various radiometer calibration parameters and part of the validation process and result