Implementation of Three Signal Acquisition Algorithms for GPS

In GPS signal processing, signal acquisition is a critical step for locating received signals and synchronizing with satellite transmissions. Three commonly used acquisition algorithms include serial search, parallel code phase search, and parallel frequency search, each optimized for different computational resources and real-time requirements.

### 1. Serial Search Serial search is the most fundamental acquisition method, which scans through possible code phases and frequency offsets sequentially to identify matching signals. Its implementation typically involves nested loops iterating over code delay bins and Doppler frequency bins, with correlation calculations performed using multiplication and integration operations. Advantages include straightforward implementation and low memory consumption; however, its slow search speed makes it unsuitable for high-dynamic environments with stringent real-time constraints.

### 2. Parallel Code Phase Search Parallel code phase search improves efficiency by processing multiple code phases simultaneously. This method commonly utilizes Fast Fourier Transform (FFT) to accelerate circular correlation calculations. The core implementation involves performing FFT on both the input signal and locally generated PRN codes, followed by inverse FFT of their product to obtain correlation peaks across all code phases. While this approach significantly reduces search time, it demands higher computational resources and memory bandwidth for FFT operations.

### 3. Parallel Frequency Search Parallel frequency search parallelizes the frequency dimension, enabling simultaneous examination of multiple frequency offset candidates. This technique is particularly suitable for handling Doppler shift variations in high-dynamic scenarios. Implementation typically involves applying FFT to time-domain signals after code stripping, allowing frequency domain analysis across multiple bins in a single operation. When combined with FFT acceleration, this method substantially improves acquisition speed, though its hardware implementation complexity makes it more appropriate for systems with strict real-time requirements.

Each algorithm possesses distinct characteristics, and practical applications should select or combine optimizations based on available computational resources, real-time demands, and signal environment conditions.