为了改善时域或频域分析的局限性,提高罗兰C的周期识别能力.在分析罗兰C信号的Wigner-Vill变换特征基础上,仿真分析了样本长度、天线输入端信噪比、天地波幅值比及天地波相位差等对罗兰C周期识别的影响。结果表明,罗兰C信号的Wigner—Vill变换峰值稳定、抗噪声性能强,利用不同天地波相位差下罗兰C信号的Wigner-Vill变换最小峰值对应的频率点不同。能够有效的实现罗兰C信号的周期识别。
For improving the limit of time domain or frequency domain analysis and the cycle identification capability for Loran-C, the effect of swatch's length, signal-to-noise ratio(SNR) at the antenna input, sky-wave to ground-wave ratio(SGR) and phase difference of sky-wave to ground-wave on cycle identification of Loran-C were analyzed and simulated based on the analysis of Loran-C signal's Wigner-Vill transformation(WVT) characters. The results show that positive peak values of Loran-C signal's WVT are steady, the transformation has good anti-noise performance, and cycle identification can be realized successfully and effectively because the frequency points corresponding to the negative peak values of Loran-C signal's WVT are different at different phase difference.