Measurement of range and speed of high-speed targets by millimeter wave pulse radar

Mogyla, A. A.; Хлопов, Г. І.

doi:10.1109/msmw.2016.7538164

Cited by 4 publications

(2 citation statements)

References 5 publications

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“…) Therefore, the one-step state prediction equation ( 10), the one-step prediction mean square error matrix (11), the Kalman filter gain matrix (15), the state estimation equation (16), and the estimated mean square error equation ( 17) have been obtained. The optimal estimation value of the altitude state can be gotten by using the above iterative equation.…”

Section: Figure 3 Algorithm Flow Chartmentioning

confidence: 99%

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Detection of crop heights by UAVs based on the Adaptive Kalman Filter

Xu¹,

Wang²,

Yang³

et al. 2018

International Journal of Precision Agricultural Aviation

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Detection of crop heights by UAVs is fast and accurate and can reflect the growth situation of crops. The core of this operation is the measurement of UAV flight altitude. In order to improve the accuracy of the response to the variation of flight altitude, a light-weight altitude detection system was developed for plant-protection UAVs. A millimeter wave radar (MWR) was used as the altitude detector. Moreover, a data fusion algorithm based on the Adaptive Kalman Filter (AKF) was developed. The altitude data by the MWR, the angle data by the Inertial Measurement Unit (IMU) and the position data by Global Positioning System (GPS) were processed by the AKF to obtain optimal updated values, and the optimal updated values was fused to establish the distribution map of crop heights. Results of the trials in the condition of the flight heights of 5 m and 10 m indicated that: 1) compared with the direct detection by the MWR, the error of detection was reduced by 0.035 m.2) compared with real crop heights, the error of detection was 0.02 m. The developed system could achieve the accurate detection of the crop height, providing a new theoretical model and technical idea for the UAVs configured for plant-protection.

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Section: Figure 3 Algorithm Flow Chartmentioning

confidence: 99%

“…Currently, there are many studies regarding the altitude detection for UAVs. Ultrasonic sensors [11] , LIDAR [12,13] , Image sensors [14] and millimetre wave radar (MWR) [15][16][17][18] are commonly used as measurement devices. Detection by a single sensor is a basic approach.…”

Section: Introductionmentioning

confidence: 99%