Operation method for FFT

Abstract

The invention provides an operation method for FFT. The method comprises the following steps: performing block floating point operation, moving data blocks leftwards or rightwards to regulate the signal power of FFT input during operation, performing data regulation according to an internal calculation result of each stage after the data operation of each stage by virtue of a special block floating point operation module, storing a set of data sharing a shift factor with an independent data field on hardware, and dividing result data by a preset gain to obtain correct data after operation, wherein the shift factors of the data blocks in block floating points are determined by maximum values of all the data in the whole data blocks. According to the floating point operation method, conflicts between a fixed-point algorithm and a floating point algorithm are solved, floating point operation efficiency is improved, and cost is lowered.

Description

technical field [0001] The invention relates to a programmable processor, in particular to an operation method for realizing FFT. Background technique [0002] In communication and radar signal processing, FFT is a commonly used tool, and it is mostly completed by FPGA when the speed requirement is relatively high or the integration degree is high. The vast majority of processors use fixed-point data format to process data, which makes the processing structure relatively simple, but the overflow phenomenon is more serious, and the use of simple fixed-point truncation will submerge small signals in large signals, making the result data Lose the necessary precision. As the requirements for data precision are getting higher and higher, the general fixed-point algorithm can no longer meet the high-precision requirements, and it is necessary to resort to floating-point processors for calculations to avoid overflow problems in applications. Most foreign FFT Cores use fixed-point...

AI Technical Summary

Problems solved by technology

Therefore, compared with fixed-point calculations, floating-point calculations have disadvantages such as difficult development, long development cycle, and high development costs.

[0003] Therefore, for the above-mentioned problems existing in related technologies, effective solutions have not yet been proposed

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