MATLAB code implements UAV trajectory tracking based on nonlinear least multiplication pseudorange data

MATLAB code implements UAV trajectory tracking based on nonlinear least multiplication pseudorange data

Unmanned aerial vehicle (UAV) trajectory tracking is one of the important tasks of UAV navigation and control. In this article, we will use MATLAB to implement a UAV trajectory tracking algorithm based on nonlinear least multiplication pseudorange data. We will introduce the principles of the algorithm and provide the corresponding MATLAB code.

Algorithm principle

The UAV trajectory tracking algorithm is based on nonlinear least multiplication pseudorange data. It mainly includes the following steps:

1. Data collection: Use sensors to obtain the position and attitude data of the drone. A Global Positioning System (GPS) receiver is usually used to obtain the global position information of the drone.

2. Pseudorange measurement: Use the received GPS signal to calculate the pseudorange measurement values ​​between the drone and multiple satellites. These pseudorange data are used to calculate the distance between the drone and the satellite.

3. Nonlinear least multiplication: Use the nonlinear least multiplication algorithm to optimize the position and attitude of the drone and the pseudorange data. This algorithm estimates the position and attitude of the UAV by minimizing the pseudorange residual.

4. Trajectory generation: Generate the trajectory of the drone based on the optimized position and attitude data. Trajectory generation can employ interpolation or smoothing algorithms to obtain smooth and continuous trajectories.

MATLAB code implementation

The following is a sample code using MATLAB to implement UAV trajectory tracking based on nonlinear least multiplication pseudorange data:

% 参数设置
numSatellites = 4; % 卫星数量
numIterations