Chen Danqi, Jin Guodong, Tan Lining, et al. Target positioning of UAV airborne optoelectronic platform based on nonlinear least squares[J]. Opto-Electronic Engineering, 2019, 46(9): 190056. doi: 10.12086/oee.2019.190056
Citation: Chen Danqi, Jin Guodong, Tan Lining, et al. Target positioning of UAV airborne optoelectronic platform based on nonlinear least squares[J]. Opto-Electronic Engineering, 2019, 46(9): 190056. doi: 10.12086/oee.2019.190056

Target positioning of UAV airborne optoelectronic platform based on nonlinear least squares

    Fund Project: Supported by National Natural Science Foundation of China (61673017, 61403398)
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  • The target positioning algorithm of the traditional unmanned aerial vehicle (UAV) airborne optoelectronic platform introduces a large number of angle measurement errors, resulting in low target positioning accuracy. In this paper, a hybrid nonlinear algorithm of least squares and Gauss-Newton is proposed. Firstly, the Gauss-Newton iterative nonlinear target localization algorithm based on laser ranging value is derived. Then the rough solution of linear least square is used as the initial value of the nonlinear Newton iteration method for target location estimation. The algorithm combines the advantages of the simple and easy implementation of the least squares method and the high convergence accuracy of the Gauss-Newton method, and satisfies the requirements of the Gauss-Newton method for the initial value accuracy. Experimental results of measured data show that the longitude error of fixed target positioning results of this method is less than 1.37×10-5 degrees, the latitude error is less than 6.31×10-5 degrees, and the height error is less than 1.78 meters. And the processing time of each positioning is within 6 ms, which meets the requirements of real-time positioning.
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  • Overview: In the past few decades, unmanned aerial vehicles (UAV) have developed rapidly, and they have been widely used in actual intelligence reconnaissance and target surveillance with their unique advantages such as zero casualties, long-term endurance, and high flexibility. Accurate positioning and tracking of battlefield targets is one of the most important military applications for UAV. At present, the traditional UAV airborne photoelectric platform target positioning algorithm is based on the single UAV photoelectric platform for angle information measurement and distance information measurement. However, the UAV attitude angle error and the photoelectric platform attitude angle error are introduced into the algorithm, which leads to the low target positioning accuracy. The target positioning method based on laser ranging value avoids the attitude angle of the UAV and the attitude angle error of the photoelectric platform in the calculation process, and has the advantages of less error source and high positioning accuracy, which is a common method for high-precision target positioning algorithm. The algorithm commonly used in target location estimation based on laser ranging values is a pseudo-linearized linear least squares method, but the pseudo-linearization process in the algorithm results in a large loss of observation accuracy, especially the target height localization precision. In this paper, a hybrid nonlinear algorithm of least squares and Gauss-Newton is proposed. The Gauss-Newton iteration method is a nonlinear algorithm with fast convergence speed and high precision, but it has certain requirements for the initial value of iteration. Therefore, this paper firstly deduces the pseudo-linearized least squares target localization algorithm, and based on this algorithm, roughly estimates the target position and obtains the coarse positioning result. Secondly, the Gauss-Newton iterative nonlinear target localization algorithm based on laser ranging value is derived. Then the linear least squares rough result is used as the initial value of the nonlinear Newton iteration method for target location estimation. The algorithm combines the advantages of the simple and easy implementation of the least squares method and the high convergence accuracy of the Gauss-Newton method, and satisfies the certain requirements of the Gauss-Newton method for the initial value accuracy. Experimental results of measured data show that the longitude error of fixed target positioning results of this method is less than 1.37×10-5 degrees, the latitude error is less than 6.31×10-5 degrees, and the height error is less than 1.78 meters. And the processing time of each positioning is within 8 ms, which meets the requirements of real-time positioning. The experimental results show that this algorithm has high engineering application value.

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