Abstract
In a global positioning system (GPS) passive radar, a high resolution requires a high sampling frequency, which increases the computational load. Balancing the computational load and the range resolution is challenging. This paper presents a method to trade off the range resolution and the computational load by experimentally determining the optimal sampling frequency through an analysis of multiple sets of GPS satellite data at different sampling frequencies. The test data are used to construct a range resolution-sampling frequency trade-off model using least-squares estimation. The theoretical analysis shows that the experimental data are the best fit using smoothing and nth-order derivative splines. Using field GPS C/A code signal-based GPS radar, the trade-off between the optimal sampling frequency is determined to be in the 20 461.25 -24 553.5 kHz range, which supports a resolution of 43–48 m. Compared with the conventional method, the CPU time is reduced by approxi-mately 50%.
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