Gradient Descent Optimization-Based SINS Self-Alignment Method and Error Analysis

In this paper, the self-alignment for stationary strapdown inertial navigation system (SINS) is formulated as an optimization problem, and two gradient descent optimization-based SINS methods (GD1 GD2) are proposed. The highlight lies in that quaternion-based objective functions firstly to solve problem. Different from conventional initial alignment methods, we construct a function using gravity, Earth rate local latitude information GD1, employs method achieve minimum of function. Secondly, further improve GD2 by measurements IMU represent instead directly. Thus, more competent when not available. addition, also analyze bias errors accelerometer gyroscope quaternion normality error GD1 respectively. Moreover, based on analysis results, scale factor introduced reduce caused biases. Simulation static experiment implemented test performances method, results verify accuracy speed proposed methods.