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Taschenbuch. Condizione: Neu. Neuware - This research effort examines the reduction of error in inertial navigation aided by vision. This is part of an effort focused on navigation in a GPS denied environment. The navigation concept examined here consists of two main steps. First, extract the position of a tracked ground object using vision and geo-locate it in 3 dimensional navigation frame. In this rst step multiple positions of the UAV are assumed known; think of a synthetic aperture. The only information about the tracked ground objects/features is the unit vector that points to the objects from the center of the camera. Two such vectors give enough information to calculate the best estimate of the position of the tracked object in a 3 dimensional navigation frame using the method of least square. Concerning the second step: checking observability for the 3-D case shows that at least 2 objects need to be tracked. In practice one needs to track more than two objects to wash out the measurement error and obtain good results.

Buch. Condizione: Neu. Neuware - This research effort examines the reduction of error in inertial navigation aided by vision. This is part of an effort focused on navigation in a GPS denied environment. The navigation concept examined here consists of two main steps. First, extract the position of a tracked ground object using vision and geo-locate it in 3 dimensional navigation frame. In this rst step multiple positions of the UAV are assumed known; think of a synthetic aperture. The only information about the tracked ground objects/features is the unit vector that points to the objects from the center of the camera. Two such vectors give enough information to calculate the best estimate of the position of the tracked object in a 3 dimensional navigation frame using the method of least square. Concerning the second step: checking observability for the 3-D case shows that at least 2 objects need to be tracked. In practice one needs to track more than two objects to wash out the measurement error and obtain good results.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

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Condizione: New. Print on Demand.

Condizione: New. Print on Demand.

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Hardcover. Condizione: new. Hardcover. This research effort examines the reduction of error in inertial navigation aided by vision. This is part of an effort focused on navigation in a GPS denied environment. The navigation concept examined here consists of two main steps. First, extract the position of a tracked ground object using vision and geo-locate it in 3 dimensional navigation frame. In this rst step multiple positions of the UAV are assumed known; think of a synthetic aperture. The only information about the tracked ground objects/features is the unit vector that points to the objects from the center of the camera. Two such vectors give enough information to calculate the best estimate of the position of the tracked object in a 3 dimensional navigation frame using the method of least square. Concerning the second step: checking observability for the 3-D case shows that at least 2 objects need to be tracked. In practice one needs to track more than two objects to wash out the measurement error and obtain good results.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.