Japan Aerospace Exploration Agency (JAXA) has developed and operated a series of passive microwave imager, called the Advanced Microwave Scanning Radiometer (AMSR) series, that to contribute to monitoring and projection of global water cycle variation and application in operational utilization. From the first generation of AMSR series, AMSR and AMSR-E, and the second generation, AMSR2, we successfully achieved to archive more than 20 years consistent and continuous data record. AMSR2 has been operating on the A-train orbit since July 2012 and it also joined to the Global Precipitation Measurement (GPM) constellations to provide valuable passive microwave observation in the afternoon orbit for producing global rainfall maps. JAXA is currently developing the third generation of AMSR series, AMSR3, with additional high-frequency channels in 166 and 183 GHz to be launched in Japanese Fiscal Year of 2024.

This paper describes current status of the level 1 algorithm development and calibration for the Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM). JAXA has carried out the calibration for the DPR since the GPM core observatory was launched on February 28, 2014 (JST). As a result of the external calibration, it is detected that some biases seemed to exist. However, JAXA has not adjusted the calibration coefficient of the DPR level 1 algorithm because of two reasons. One is the errors of the external calibration. In the external calibration, the measurement error and estimation error for the power may occur. The other reason is the continuity of the surface backscattering cross section (denoted as σ0) from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). Requirement of the continuity has been satisfied by using the current calibration coefficient.

The Dual-frequency Precipitation Radar (DPR) installed on the Global Precipitation Measurement (GPM) core satellite was developed by JAXA and NICT. This paper describes mission objectives, technical performance, resource allocation, design, proto-flight test (PFT) of the DPR instrument, satellite system test including launch operations and orbital check out results of the DPR. The DPR system PFT has completed in February 2012. DPR has handed over to NASA and integration of the DPR to the GPM core spacecraft have completed in May 2012. GPM core spacecraft satellite system test has completed at NASA Goddard Space Flight Center. GPM core observatory was shipped to JAXA Tanegashima Space Center, JAPAN and Launch Site Operations has completed. GPM core observatory was successfully launched by H-IIA launch vehicle on Feb 28, 2014. DPR orbital check out had started in March 2014 and it was completed in May 2014. The orbital check out results of DPR is reported in this paper.

The Global Precipitation Measurement (GPM) mission consists of the GPM core Observatory (satellite) and the constellation satellites. The GPM core Observatory launched at 3:37 on February 28, 2014 (JST) from Tanegashima Space Center in Japan. It carries the Dual-frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI). The DPR consists of Ku-band precipitation radar (KuPR) and Ka-band precipitation radar (KaPR). These radars have developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT) [1] and GMI has developed by National Aeronautics and Space Administration (NASA). The DPR level 1 algorithm has been developed by the JAXA. The main roles of level 1 algorithm are limit check for fatal and caution incidents, orbital cut and calculation of geometric information and transformation for engineering value. JAXA also has the responsibility of calibration of the DPR. The calibration methods have two types. One is the internal calibration with onboard calibration system, and the other is the external calibration with Active Radar Calibrator (ARC). These calibrations will carry out densely by the public data release. This paper describes the concepts of the level 1 algorithm and the calibration methods.

The Dual-frequency Precipitation Radar (DPR) installed on the Global Precipitation Measurement (GPM) core satellite is being developed by JAXA and NICT. This paper describes mission objectives, technical performance, resource allocation, critical design, proto-flight test (PFT) of the DPR instrument and satellite system test status. The DPR system PFT has completed in February 2012. DPR has handed over to NASA and integration of the DPR to the GPM core spacecraft have completed in May 2012. GPM core spacecraft satellite system test has started at NASA Goddard Space Flight Center. After completion of all satellite system tests, the GPM core spacecraft will be sent to JAXA Tanegashima Space Center and launched by H-IIA launch vehicle.

Extreme diversities, versatility and dynamism of cloud computing applications with its high availability through smart devices such as smart phones and media are shown to be supported by the cyber world modeling in an incrementally modular abstraction hierarchy (IMAH) with homotopy extension property (HEP) and homotopy lifting property (HLP), as a transparent and highly universal modeling of smart cloud computing businesses to overcome combinatorial explosion of smart computing. It works to realize cost effective and visible businesses with high social impacts, both globally and locally, contributing to clarify smart cloud computing in the smart cloud imagery business.

The Dual-frequency Precipitation Radar (DPR) installed on the Global Precipitation Measurement (GPM) core satellite is being developed by JAXA and NICT. This paper describes objectives, technical performance, resource allocation, preliminary design, development model test, critical design and proto-flight test (PFT) of the DPR instrument. The DPR system PFT will be completed in 2011. After completion of all PFT, the DPR instrument will be verified as a space borne radar.

It has been recognized that the design of similarity measures to compare multiple motion-capture (mocap) data streams is one of the major tasks in human motion analysis [Müller et al. 2008]. The information of similarity is utilized for many applications such as the retrieval of mocap data streams.