170 lines
5.0 KiB
C
170 lines
5.0 KiB
C
/*
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* Copyright (c) 2008, Swedish Institute of Computer Science
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* 3. Neither the name of the Institute nor the names of its contributors
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* may be used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE INSTITUTE AND CONTRIBUTORS ``AS IS'' AND
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* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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* ARE DISCLAIMED. IN NO EVENT SHALL THE INSTITUTE OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
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* OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
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* HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
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* OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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* SUCH DAMAGE.
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*
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* -----------------------------------------------------------------
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* ifft - Integer FFT (fast fourier transform) library
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*
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*
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* Author : Joakim Eriksson
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* Created : 2008-03-27
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* Updated : $Date: 2008/07/03 23:40:12 $
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* $Revision: 1.3 $
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*/
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#include "contiki.h"
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#include "lib/ifft.h"
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/*---------------------------------------------------------------------------*/
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/* constant table of sin values in 8/7 bits resolution */
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/* NOTE: symmetry can be used to reduce this to 1/2 or 1/4 the size */
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#define SIN_TAB_LEN 120
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#define RESOLUTION 7
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static const int8_t SIN_TAB[] = {
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0,6,13,20,26,33,39,45,52,58,63,69,75,80,
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85,90,95,99,103,107,110,114,116,119,121,
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123,125,126,127,127,127,127,127,126,125,
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123,121,119,116,114,110,107,103,99,95,90,
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85,80,75,69,63,58,52,45,39,33,26,20,13,6,
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0,-6,-13,-20,-26,-33,-39,-45,-52,-58,-63,
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-69,-75,-80,-85,-90,-95,-99,-103,-107,-110,
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-114,-116,-119,-121,-123,-125,-126,-127,-127,
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-127,-127,-127,-126,-125,-123,-121,-119,-116,
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-114,-110,-107,-103,-99,-95,-90,-85,-80,-75,
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-69,-63,-58,-52,-45,-39,-33,-26,-20,-13,-6
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};
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static uint16_t bitrev(uint16_t j, uint16_t nu)
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{
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uint16_t k;
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k = 0;
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for (; nu > 0; nu--) {
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k = (k << 1) + (j & 1);
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j = j >> 1;
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}
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return k;
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}
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/* Non interpolating sine... which takes an angle of 0 - 999 */
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static int16_t sinI(uint16_t angleMilli)
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{
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uint16_t pos;
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pos = (uint16_t) ((SIN_TAB_LEN * (uint32_t) angleMilli) / 1000);
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return SIN_TAB[pos % SIN_TAB_LEN];
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}
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static int16_t cosI(uint16_t angleMilli)
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{
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return sinI(angleMilli + 250);
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}
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static uint16_t ilog2(uint16_t val)
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{
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uint16_t log;
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log = 0;
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val = val >> 1; /* The 20 = 1 => log = 0 => val = 0 */
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while (val > 0) {
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val = val >> 1;
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log++;
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}
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return log;
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}
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/* ifft(xre[], n) - integer (fixpoint) version of Fast Fourier Transform
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An integer version of FFT that takes in-samples in an int16_t array
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and does an fft on n samples in the array.
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The result of the FFT is stored in the same array as the samples
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was stored. Them imaginary part of the result is stored in xim which
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needs to be of the same size as xre (e.g. n ints).
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Note: This fft is designed to be used with 8 bit values (e.g. not
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16 bit values). The reason for the int16_t array is for keeping some
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'room' for the calculations. It is also designed for doing fairly small
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FFT:s since to large sample arrays might cause it to overflow during
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calculations.
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*/
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void
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ifft(int16_t xre[], int16_t xim[], uint16_t n)
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{
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uint16_t nu;
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uint16_t n2;
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uint16_t nu1;
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int p, k, l, i;
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int32_t c, s, tr, ti;
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nu = ilog2(n);
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nu1 = nu - 1;
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n2 = n / 2;
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for (i = 0; i < n; i++)
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xim[i] = 0;
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for (l = 1; l <= nu; l++) {
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for (k = 0; k < n; k += n2) {
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for (i = 1; i <= n2; i++) {
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p = bitrev(k >> nu1, nu);
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c = cosI((1000 * p) / n);
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s = sinI((1000 * p) / n);
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tr = ((xre[k + n2] * c + xim[k + n2] * s) >> RESOLUTION);
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ti = ((xim[k + n2] * c - xre[k + n2] * s) >> RESOLUTION);
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xre[k + n2] = xre[k] - tr;
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xim[k + n2] = xim[k] - ti;
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xre[k] += tr;
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xim[k] += ti;
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k++;
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}
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}
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nu1--;
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n2 = n2 / 2;
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}
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for (k = 0; k < n; k++) {
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p = bitrev(k, nu);
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if (p > k) {
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n2 = xre[k];
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xre[k] = xre[p];
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xre[p] = n2;
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n2 = xim[k];
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xim[k] = xim[p];
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xim[p] = n2;
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}
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}
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/* This is a fast but not 100% correct magnitude calculation */
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/* Should be sqrt(xre[i]^2 + xim[i]^2) and normalized with div. by n */
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for (i = 0, n2 = n / 2; i < n2; i++) {
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xre[i] = (ABS(xre[i]) + ABS(xim[i]));
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}
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}
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