福田 盛介

<p>SLIM (Smart Lander for Investigating Moon) is the Lunar Landing Demonstrator which is under development at ISAS/JAXA. SLIM demonstrates not only so-called Pin-Point Landing Technique to the lunar surface, but also demonstrates the design to make the explorer small and lightweight. Realizing the compact explorer is one of the key points to achieve the frequent lunar and planetary explorations. This paper summarizes the preliminary system design of SLIM, especially the way to reduce the size.</p>

For planetary exploration missions using a lander, autonomous pinpoint landing capability whose precision is less than 100-meter must be needed in order to land on limited investigation areas. This capability cannot be realized with an inertial navigation system in terms of accuracy, so that the inertial error should be reduced in some way. One of solutions is image-based velocity measurement in a navigation path of the planetary lander. However, images taken by the lander have probrems such as frame rate limit and motion blur. Moreover, the available onboard resources of computation are limited. This paper proposes a velocity estimation method using a single blurred image for the pinpoint planatary landing. We present the method based on cepstral analysis and discuss feasibility through resource evaluation with a space-grade FPGA.

In recent years, investigating moon is once again drawing attentions of several countries. In Japan, an image-based autonomous navigation method is studied for a moon investigating project by the small lunar lander. The purpose of this paper is to propose a safe landing areas detection method for lunar environmental suitability that uses brightness values and to propose a landing point determination algorithm in a limited calculating area for the actual lunar lander. In addition, we study acceleration of the processing speed for hardware implementation and robustness of the proposed method.

<p>In this study, a crater detection method for a moon-landing system with low computational resources is proposed. The proposed method is applied to the Smart Lander for Investigating Moon (SLIM), which aims for a pin-point landing on the moon. According to this plan, surface images of the moon will be captured by a camera mounted on the space probe, and the craters are to be detected from the images. Based on the positional relationship between detected craters, the method estimates the exact flight position of the space probe. Because the computational resources of SLIM are limited, rapid and accurate crater detection must be performed using fixed-point arithmetic on a field-programmable gate array (FPGA). This study proposes a crater detection method that uses principal component analysis (PCA). The computational processing for crater detection by PCA is performed by product-sum operations, which are suitable for fixed-point arithmetic. Moreover, this method is capable of parallel processing; hence high-speed processing is expected. This study not only introduces a crater detection method using PCA but also evaluates the properties of this method.</p>

We are in progress to develop a system for automatic operation of a satellite in order to reduce human load at satellite steady operation phase. The ground station for small satellite REIMEI (INDEX : INnovative-technology Demonstration EXperiment) is used as a test bench for verification of the proposed method. In our new automatic operation system, a scheduler software as a substitutive operator manages all the operations through a unified procedure, including sending command, receiving telemetry, and driving antenna in accordance with an operation time line which is prepared before the operation pass. The scheduler also performs diagnostics of satellite anomaly based upon the received telemetry data and status of the ground station. In case that some anomaly of the satellite is detected, the scheduler initiates an emergency schedule that was prepared depending on the emergency level. The automatic operation system is nearly completed for downlink operations of the data recorder that account for 75% of REIMEI steady operation. This approach is very effective to reduce psychological and physical load of operators.

本論文は,高分解能な合成開口レーダ(Synthetic Aperture Radar : SAR)画像のスペックル低減処理において,テクスチャやエッジなどの特徴量を保存する手法を提案している.提案する手法は,Gamma-Gamma MAPフィルタにおける局所領域からのオーダパラメータの推定に際して,オーダパラメータの推定精度を向上させるために,比較的広い領域を選択し,注目画素と同様の性質を有する領域に含まれる画素で構成されるウィンドウを新たに設定し,得られたウィンドウ内に含まれる画素を用いて,オーダパラメータを推定する.得られたオーダパラメータを基に,事後最大確率推定を行うことで,同一領域におけるテクスチャ情報を保持しつつ,スペックルを低減する.計算機シミュレーション画像による性能評価により,特徴量の保持性能と平滑性能を確認した上で,実際のSAR画像に適用することにより,従来手法と比較して高い視覚的自然性を確認した.

The Institute of Space and Astronautical Science JAXA is developing a landing radar comprising a radio altimeter and a velocity meter, which are two of the mandatory navigation sensors for a planetary lander. A BBM of the landing radar has been evaluated on natural terrains by using a helicopter. This paper introduces the BBM hardware and discusses the dynamic performance in field experiments.