MATLAB Implementation of GPS Software Receiver

A GPS software receiver is a receiver system that implements GPS signal processing through software, utilizing tools like MATLAB to complete the entire process from signal acquisition to position calculation. Compared to traditional hardware receivers, software receivers offer advantages such as greater flexibility and lower development costs.

Signal acquisition is the first step in a software receiver, primarily aimed at detecting visible satellites and roughly estimating Doppler frequency shift and code phase. In MATLAB implementation, methods like parallel frequency search or parallel code phase search are typically employed, achieving rapid signal acquisition through correlation operations. The acquisition process requires consideration of local carrier and pseudo-random noise (PRN) code generation, along with correlation peak detection strategies. Code implementation often involves generating replica signals and computing cross-correlation matrices to identify synchronization points.

Signal tracking is a critical follow-up stage after acquisition, focused on precisely tracking and synchronizing the detected satellite signals. In MATLAB implementations, Delay Locked Loops (DLL) and Phase Locked Loops (PLL) are commonly used to track code phase and carrier phase respectively. The DLL adjusts the phase of local PRN codes to align with received signals, while the PLL tracks carrier frequency variations to ensure accurate signal demodulation. Algorithm implementation typically includes discriminator functions for error measurement and loop filters for smooth parameter adjustments.

Pseudorange calculation forms the foundation of GPS positioning, derived by multiplying signal transmission time by the speed of light to determine the pseudorange between satellites and receivers. During MATLAB implementation, this requires combining code phase and carrier phase information from tracking loops with satellite positions decoded from navigation data to compute actual pseudorange observations. This involves precise timestamp handling and geometric range calculations.

The position calculation phase utilizes pseudorange observations and satellite ephemeris data to compute receiver position, velocity, and time (PVT) through least squares methods or Extended Kalman Filters (EKF). In MATLAB, this process typically involves constructing satellite geometry matrices, applying error corrections (such as ionospheric and tropospheric delays), and iteratively solving for receiver coordinates. Implementation details include weight matrix configuration for observation quality and convergence criteria for iterative algorithms.

The MATLAB implementation of GPS software receivers not only facilitates learning and research into GPS signal processing workflows but also serves as a foundation for further optimization and algorithm validation. By adjusting acquisition strategies, improving tracking loops, or optimizing position calculation algorithms, the accuracy and stability of receivers can be significantly enhanced. Code modularity allows for independent testing of signal processing components and integration of advanced navigation algorithms.