Satellite Pseudorange Positioning with MATLAB Implementation

In satellite pseudorange positioning, GPS positioning methods vary depending on the measurement approach employed. Under hypothetical error-free conditions, MATLAB can convert the positioning problem into a nonlinear equation system, which can be solved using numerical methods such as the fsolve function or custom iterative algorithms. However, in practical applications, errors are inevitable. To enhance satellite positioning accuracy, multiple error reduction methods can be implemented. For instance, differential GPS can be programmed in MATLAB to eliminate most common errors through reference station corrections. Additionally, Kalman filtering algorithms can process GPS data streams to reduce noise and improve precision, implemented using functions like kalman or custom state-space models. GNSS signal processing techniques, along with other advanced processing methods, can also be integrated into MATLAB workflows. Therefore, in satellite pseudorange positioning, there are numerous areas for exploration and optimization to improve positioning accuracy. MATLAB implementations may include signal correlation techniques, ionospheric delay modeling, and multipath error mitigation algorithms, all contributing to more robust positioning solutions.