In a global positioning system(GPS)passive radar,a high resolution requires a high sampling frequency,which in-creases 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 computation-al load by experimentally determining the optimal sampling fre-quency through an analysis of multiple sets of GPS satellite data at different sampling frequencies.The test data are used to con-struct a range resolution-sampling frequency trade-off model us-ing 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 fre-quency 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%.