A Random Noise Filtering Method for Specific Signals

Abstract

A specific signal random noise filtering method is provided; a conventional method comprises the following steps: assuming an observed value Am is the true value Zm according to the observed value Am; using a mapping relation f(m-n) to obtain a guess value Tm-n=Am+f(m-n) with certain precision; because random noise is stacked on the observed value Am, so the guess value Tm-n may have large deviations, or larger and larger deviations can be accumulated with the increasing of guess points. The filtering algorithm uses the basic principle that the observed value Am is assumed to be equal to Zm, so the difference value between a series of guess values obtained according to the observed value Am and the observed value should be equal to the random noise rm, and the amplitude 80% will fall into the range of [-R R]; increment or decrement adjustment are carried out for the Tm according to whether the difference value exceeds the [-R R] or not, and the Tm will more and more approach to Zm along with the increasing adjustments.

Description

technical field [0001] The invention relates to the field of signal processing, in particular to a random noise filtering method for a specific signal. Background technique [0002] In the field of time service, whether it is Beidou time service, GPS time service, GLONASS time service, PTP time service, long-wave time service or short-wave time service, use wireless or wired channels for time and frequency transmission, because the receiver clock is unstable, the system clock difference, and the delay of the transmission channel Due to factors such as jitter, the timing information restored by the receiver often has a certain random jitter. In the field of passive positioning, the arrival time of received time pulses in the time domain often fluctuates greatly due to changes in signal strength. [0003] The traditional linear filtering method can effectively filter out random noise, but at the same time, some useful components of gradual changes are also passivated and beco...

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Problems solved by technology

[0003] The traditional linear filtering method can effectively filter out random noise, but at the same time, some useful components of gradual changes are also passivated and become insensitive, such as the gradual change of timing information caused by the clock difference of the timing system, such as in passive positioning. Gradual change in pulse arrival time due to the Doppler effect

Traditional linear filtering methods such as Kalman filtering have better results only for linear signals

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