摘要：【中文】本发明提出了一种基于格型滤波Burg谱估计算法的低轨卫星多普勒频偏捕获方法，该方法利用Burg算法对接收信号的功率谱进行估计，在低信噪比下估计分辨率和精度比基于快速傅里叶变换的周期图法高，另外，所提出的基于格型滤波的Burg谱估计算法利用了格型滤波器的时间迭代思想，通过引入遗忘因子，将传统Burg算法的块处理方式转变为流处理方式，在每个采样点更新一次自适应回归模型参数，且仅需要用到前一个采样点的相关计算结果，整个计算过程随着时间而迭代进行，因此能够随着多普勒频偏的变化自适应调整AR模型参数，从而适用于低轨卫星多普勒时变的场景，并且这种流处理方式也易于在现场可编程门阵列中实现。 【EN】The invention provides a low orbit satellite Doppler frequency offset capturing method based on a lattice filtering Burg spectrum estimation algorithm, the method utilizes the Burg algorithm to estimate the power spectrum of the received signal, the estimation resolution and precision are higher than those of a periodogram method based on fast Fourier transform under low signal-to-noise ratio, in addition, the proposed Burg spectrum estimation algorithm based on lattice filtering utilizes the time iteration idea of lattice filters, by introducing a forgetting factor, the block processing mode of the traditional Burg algorithm is converted into a stream processing mode, the parameters of the self-adaptive regression model are updated once at each sampling point, and only the correlation calculation result of the previous sampling point is needed, the whole calculation process is iterated along with the time, so that the parameters of the AR model can be self-adaptively adjusted along with the change of Doppler frequency offset, therefore, the method is suitable for low-orbit satellite Doppler time-varying scenes, and the stream processing mode is easy to realize in a field programmable gate array.

摘要：【中文】本申请公开了一种多普勒频偏处理方法、装置及终端。方法包括：基于预设的功率谱估计算法，确定待处理的接收信号的各个采样点各自的功率谱；对接收信号的各个采样点各自的功率谱进行频谱峰值搜索处理，确定接收信号的各个采样点各自对应的谱峰；对接收信号的各个采样点各自对应的谱峰进行平滑滤波处理。本申请现有技术中需要依赖辅助数据或者需要进行符号定时恢复导致的多普勒频偏估计运算量大且准确率低的问题，进而提高了接收机后续对信号的处理精度。 【EN】The application discloses a Doppler frequency offset processing method, a device and a terminal. The method comprises the following steps: determining respective power spectrums of all sampling points of a received signal to be processed based on a preset power spectrum estimation algorithm; carrying out spectrum peak value search processing on respective power spectrums of each sampling point of the received signal, and determining respective corresponding spectrum peaks of each sampling point of the received signal; and carrying out smooth filtering processing on the spectral peaks corresponding to the sampling points of the received signal. The method and the device have the advantages that in the prior art, the problems of large calculation amount and low accuracy of Doppler frequency offset estimation caused by the need of depending on auxiliary data or the need of carrying out symbol timing recovery are solved, and then the subsequent signal processing precision of a receiver is improved.

摘要：【中文】本发明公开了一种SNR估计方法，其中该SNR估计方法包括将输入信号转变为待估计加噪信号；通过软件仿真来确定待估计加噪信号的切换阈值；通过ECF算法来计算待估计加噪信号的信噪比估计值；将估计值与阈值进行比较：如果估计值小于阈值，则保留估计值；如果估计值不小于阈值，则通过SVR算法来计算待估计加噪信号的信噪比估计值。本发明还公开了一种SNR估计系统。该SNR估计系统和SNR估计方法能够适用于高信噪比和低信噪比范围，估计范围广、精度高。 【EN】The invention discloses an SNR estimation method, wherein the SNR estimation method comprises the steps of converting an input signal into a noise signal to be estimated; determining a switching threshold value of a noise adding signal to be estimated through software simulation; calculating a signal-to-noise ratio estimation value of a noise signal to be estimated through an ECF algorithm; comparing the estimate to a threshold: if the estimated value is less than the threshold value, retaining the estimated value; and if the estimated value is not less than the threshold value, calculating the signal-to-noise ratio estimated value of the noise-added signal to be estimated through an SVR algorithm. The invention also discloses an SNR estimation system. The SNR estimation system and the SNR estimation method can be suitable for the ranges of high signal-to-noise ratio and low signal-to-noise ratio, and are wide in estimation range and high in precision.