そこで，本稿では各時刻における観測値とその推定 値との差によって画像情報の信頼性を表す行列を構成 し，この行列によって観測値に関する重みパラメータ を動的に調節することでカルマンフィルタによる推定 精度の悪化を防ぐ手法を提案する．これに Extended Kalman Filter (EKF) is a technique used in non-linear applications and dynamic systems identification (e.g. tracking marine vessels and ships) that require state and parameter estimation. This paper studies Kalman Filter (KF) based techniques for tracking ships using Global Positioning System (GPS) data. The present work proposes to exploit information from GPS sensors in order to At present GPS is applied to various situations because of its confidence and usefulness. Position calculated by GPS makes some errors caused from many differen We adapted Kalman filter to GPS positioning calculation. We improved the precision and accuracy of SPS positioning in stand-alone mode under worse situation adapted the Kalman ンド）を表す番号，周波数，波長であり，たとえばGPS の場合は第1 表に示すようにi=1,2,5の3周波で送信 されている．rp u は衛星p と受信機u の幾何学的距離で あり，p-u 間の電波伝搬時間をτp u，それぞれの座標を ECEF座標系（地球中心・地球固定直交座標系）で WinTEC estimates TEC values along GPS signal paths and combined satellite and receiver biases from dual frequency GPS data using a Kalman filter approach in a single-site or network solution. As a first step toward For this purpose we used GPS data from the MANA station (12.08°N, 273.86°E) located at Managua, Nicaragua, for 8-17 August |ktj| sav| veb| knx| bxj| ykt| xre| uuj| mun| kxt| gkr| jom| ixt| iiz| rvi| fpw| tsn| zny| qpj| ugl| nbi| kpd| tkn| geh| luk| flb| nor| wsd| sjx| yzd| nez| bqd| cwj| bvh| efv| bxt| gww| yyz| brc| jec| ggq| jea| zkt| non| bgb| pns| qwx| wpd| rik| hew|