Improvement of altitude precision in indoor and urban canyon navigation for small flying vehicles

Petritoli, Enrico; Leccese, Fabio

doi:10.1109/metroaerospace.2015.7180626

Cited by 39 publications

(23 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The third sensor oriented in Z axis should indicate the gravity acceleration value g. In the case of a non-horizontal position of the system, the gravity acceleration will affect all sensors (axis), the sensors will indicate acceleration according to the system inclination. In this case the orientation of the measuring system in its initial position will be determined using equation (5) and (6) [15], [17], [18], [19]: The utilization of magnetometers enables both the absolute orientation of the measuring system and the correction of errors in the orientation of the system. Error correction should be realized in a standstill of the system (when the algorithm identifies the application of the CP model).…”

Section: B Velocity and Direction Of The Movement Of The Systemmentioning

confidence: 99%

“…The dynamic behaviour of the system movement could be categorized to a small number of classes with different conditions -constant position (CP), constant acceleration (CA), constant velocity (CV) and rotation with constant angular velocity (CT). The signal in different classes will be processed by algorithm based on the appropriate theoretical model [10], [12], [13], [14], [16], [17], [19]. The main contribution of the paper is the new data processing model, which effectively combines above mentioned models in one robust model.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Systematic Error Elimination Using Additive Measurements and Combination of Two Low Cost IMSs

2016

View full text Add to dashboard Cite

Inertial measuring systems (IMSs) enable determination of 3D position and trajectory on a base of the actual measured acceleration and angular velocity. Measurements with the inertial sensors are influenced by errors from used sensors. Because of the principle of calculation of a position based on the recursive algorithm there is an accumulation of systematic error, which causes a rapid decreasing of the position accuracy hand in hand with a measuring time. The paper deals with the suggestion of the model for data processing, which enables to eliminate systematic errors of sensors; thereby the position accuracy is increased. For this purpose, an optical rotational-speed sensor was introduced and the additional measurement was realized with it in combination with the two IMSs located on the common baseline. Measurements from optical RPM were used in a combination with the accelerometers for their higher long-term accuracy. This combination enables to eliminate errors from the accelerometers even after the first integration process. Using the pair of IMSs located on the common baseline the requirements (constraints) of the geometric relation of two coordinate systems of these IMSs were implemented into the model for data processing. These constraints were applied for correction of the position and orientation. As a part of the suggested model an algorithm for identification of the dynamic phases was realized. This algorithm identified an actual dynamic phase of the system on a basis of the actual measured acceleration and angular velocity. This information was used for an adjustment of the processing model.Index Terms-dynamic model, inertial measurement system, optical rotational-speed sensor (RPM).

show abstract

Section: B Velocity and Direction Of The Movement Of The Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Systematic Error Elimination Using Additive Measurements and Combination of Two Low Cost IMSs

2016

View full text Add to dashboard Cite

show abstract

“…Once the relative position of the satellite with respect to the UAV is represented in the UAV's body-frame coordinates, the satellite elevation with respect to antenna bore-sight angle is calculated using the tangent inverse as shown in Equation (4).…”

Section: Satellite Elevation Angle With Respect To Antenna Bore-sight αmentioning

confidence: 99%

“…Furthermore, for many applications, GPS-only attitude estimates could eliminate the need for carrying and integrating an IMU within the navigation system. That said, it is important to acknowledge that IMU systems have become extremely lightweight and cost-effective for integration with GPS on small UAV navigation systems [2][3][4]. However, the availability of GPS-only based attitude estimates double be used as an additional information source within a fault-tolerant estimation algorithm, such as Gu.…”

Section: Introductionmentioning

confidence: 99%

Fixed-Wing UAV Attitude Estimation Using Single Antenna GPS Signal Strength Measurements

Gross

Rhudy

2016

Aerospace

View full text Add to dashboard Cite

This article considers a novel approach to using global positioning system (GPS) signal strength readings and estimated velocity vector for estimating the attitude of a small fixed-wing unmanned aerial vehicle (UAV). This approach has the benefit being able to estimate full position, velocity and attitude states of a UAV using only the data from a single GPS receiver and antenna. Two different approaches for utilizing GPS signal strength within measurement updates for UAV attitude in a nonlinear Kalman filter are discussed and assessed using recorded UAV flight data. Comparisons of UAV pitch and roll estimates against measurements from a high-grade mechanical gyroscope are used to show that approximately 5°error with respect to both mean and standard-deviation on both axes is achievable.

show abstract

“…Inertial navigation systems (INSs) are employed throughout all branches of the military and in many civil platforms, due to their significant advantages of providing continuous position, velocity and attitude information, and being invulnerable to external interference [1]. In the procedure of real-time navigation, the gravity acceleration is one of the significant pieces of external reference information needed for INSs [2].…”

Section: Introductionmentioning

confidence: 99%

An Online Gravity Modeling Method Applied for High Precision Free-INS

Wang

Yang

et al. 2016

Sensors

View full text Add to dashboard Cite

For real-time solution of inertial navigation system (INS), the high-degree spherical harmonic gravity model (SHM) is not applicable because of its time and space complexity, in which traditional normal gravity model (NGM) has been the dominant technique for gravity compensation. In this paper, a two-dimensional second-order polynomial model is derived from SHM according to the approximate linear characteristic of regional disturbing potential. Firstly, deflections of vertical (DOVs) on dense grids are calculated with SHM in an external computer. And then, the polynomial coefficients are obtained using these DOVs. To achieve global navigation, the coefficients and applicable region of polynomial model are both updated synchronously in above computer. Compared with high-degree SHM, the polynomial model takes less storage and computational time at the expense of minor precision. Meanwhile, the model is more accurate than NGM. Finally, numerical test and INS experiment show that the proposed method outperforms traditional gravity models applied for high precision free-INS.

show abstract

Improvement of altitude precision in indoor and urban canyon navigation for small flying vehicles

Cited by 39 publications

References 5 publications

Systematic Error Elimination Using Additive Measurements and Combination of Two Low Cost IMSs

Systematic Error Elimination Using Additive Measurements and Combination of Two Low Cost IMSs

Fixed-Wing UAV Attitude Estimation Using Single Antenna GPS Signal Strength Measurements

An Online Gravity Modeling Method Applied for High Precision Free-INS

Contact Info

Product

Resources

About