Pulse data compression sampling method

Abstract

The invention discloses a pulse data compression sampling method. The method comprises a compression step and a sampling step. In the compression step, firstly, a pulse interval difference value sequence is calculated, and an initial value of an intermediate circulation variable is calculated by using the pulse interval difference value sequence; secondly, a final reduction ratio standard value iscalculated by utilizing a loop iteration method; all element values of the pulse interval difference value sequence are divided by a final reduction ratio standard value, and rounding is performed according to rounding off to obtain a compressed integer pulse interval difference value sequence; and finally, the compressed integer pulse arrival time sequence is restored by using the compressed integer pulse interval difference sequence. In the sampling step, an appropriate compression sampling interval value is selected, the compressed sampling interval value is taken as a time interval to form a sparse and compressed integer time sequence with a binary amplitude; the problems of unstable pulse sequence characteristics, large calculation amount, high calculation complexity and the like caused by different sampling intervals in the prior art are solved.

Description

technical field [0001] The invention belongs to the technical field of data sampling, in particular to a pulse data compression sampling method. Background technique [0002] In the prior art, since there is no integer period dictionary and a suitable period estimation method for the integer period sequence, the pulse time-of-arrival TOA sequence is not compressed into an integer sequence for period estimation. Compressing the time-of-arrival TOA sequence into an integer sequence will lose the accuracy of the sequence period estimation if the general sequence period estimation method is used. This makes the sequence period estimation imprecise. Therefore, prior to sequence period estimation, a method is needed to transform the original pulse time-of-arrival TOA sequence into a compressed, sparse, integer time sequence with binary amplitudes. The primary task of extracting the period of the sequence is compressed sampling. A suitable compressed sampling can not only reduce ...

AI Technical Summary

Problems solved by technology

For a pulse sequence with a wide frequency band, if the sampling interval is greater than the width of some small periods, the pulse sequence with a small period will be ignored, which will reduce the number of cycles of the original aliased pulse sequence

For the staggered pulse sequence, the number of staggered sub-periods will be reduced

If the sampling interval is small, it will increase the operation of the dictionary and increase the complexity of the algorithm

Therefore, there is an urgent need for a pulse data compression sampling method to overcome the problems of unstable pulse sequence characteristics, large amount of calculation, and high computational complexity caused by different sampling intervals in the prior art.

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