5 changed files with 255 additions and 2 deletions
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/*
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* This file is free software: you can redistribute it and/or modify it |
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* under the terms of the GNU General Public License as published by the |
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* Free Software Foundation, either version 3 of the License, or |
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* (at your option) any later version. |
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* |
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* This file is distributed in the hope that it will be useful, but |
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* WITHOUT ANY WARRANTY; without even the implied warranty of |
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
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* See the GNU General Public License for more details. |
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* |
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* You should have received a copy of the GNU General Public License along |
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* with this program. If not, see <http://www.gnu.org/licenses/>.
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* |
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* Code by Andy Piper |
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*/ |
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#include <AP_HAL/AP_HAL.h> |
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#include "AP_HAL_SITL.h" |
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#include <AP_Math/AP_Math.h> |
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#include <GCS_MAVLink/GCS.h> |
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#include "DSP.h" |
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#include <cmath> |
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using namespace HALSITL; |
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extern const AP_HAL::HAL& hal; |
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// The algorithms originally came from betaflight but are now substantially modified based on theory and experiment.
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// https://holometer.fnal.gov/GH_FFT.pdf "Spectrum and spectral density estimation by the Discrete Fourier transform (DFT),
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// including a comprehensive list of window functions and some new flat-top windows." - Heinzel et. al is a great reference
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// for understanding the underlying theory although we do not use spectral density here since time resolution is equally
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// important as frequency resolution. Referred to as [Heinz] throughout the code.
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// initialize the FFT state machine
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AP_HAL::DSP::FFTWindowState* DSP::fft_init(uint16_t window_size, uint16_t sample_rate) |
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{ |
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DSP::FFTWindowStateSITL* fft = new DSP::FFTWindowStateSITL(window_size, sample_rate); |
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if (fft->_hanning_window == nullptr || fft->_rfft_data == nullptr || fft->_freq_bins == nullptr) { |
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delete fft; |
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return nullptr; |
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} |
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return fft; |
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} |
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// start an FFT analysis
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void DSP::fft_start(AP_HAL::DSP::FFTWindowState* state, const float* samples, uint16_t buffer_index, uint16_t buffer_size) |
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{ |
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step_hanning((FFTWindowStateSITL*)state, samples, buffer_index, buffer_size); |
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} |
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// perform remaining steps of an FFT analysis
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uint16_t DSP::fft_analyse(AP_HAL::DSP::FFTWindowState* state, uint16_t start_bin, uint16_t end_bin, uint8_t harmonics, float noise_att_cutoff) |
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{ |
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FFTWindowStateSITL* fft = (FFTWindowStateSITL*)state; |
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step_fft(fft); |
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step_cmplx_mag(fft, start_bin, end_bin, harmonics, noise_att_cutoff); |
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return step_calc_frequencies(fft, start_bin, end_bin); |
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} |
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// create an instance of the FFT state machine
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DSP::FFTWindowStateSITL::FFTWindowStateSITL(uint16_t window_size, uint16_t sample_rate) |
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: AP_HAL::DSP::FFTWindowState::FFTWindowState(window_size, sample_rate) |
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{ |
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if (_freq_bins == nullptr || _hanning_window == nullptr || _rfft_data == nullptr) { |
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gcs().send_text(MAV_SEVERITY_WARNING, "Failed to allocate window for DSP"); |
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return; |
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} |
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buf = new complexf[window_size]; |
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} |
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DSP::FFTWindowStateSITL::~FFTWindowStateSITL() |
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{ |
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delete[] buf; |
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} |
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// step 1: filter the incoming samples through a Hanning window
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void DSP::step_hanning(FFTWindowStateSITL* fft, const float* samples, uint16_t buffer_index, uint16_t buffer_size) |
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{ |
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// 5us
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// apply hanning window to gyro samples and store result in _freq_bins
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// hanning starts and ends with 0, could be skipped for minor speed improvement
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const uint16_t ring_buf_idx = MIN(buffer_size - buffer_index, fft->_window_size); |
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mult_f32(&samples[buffer_index], &fft->_hanning_window[0], &fft->_freq_bins[0], ring_buf_idx); |
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if (buffer_index > 0) { |
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mult_f32(&samples[0], &fft->_hanning_window[ring_buf_idx], &fft->_freq_bins[ring_buf_idx], fft->_window_size - ring_buf_idx); |
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} |
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} |
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// step 2: performm an in-place FFT on the windowed data
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void DSP::step_fft(FFTWindowStateSITL* fft) |
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{ |
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for (uint16_t i = 0; i < fft->_window_size; i++) { |
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fft->buf[i] = complexf(fft->_freq_bins[i], 0); |
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} |
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calculate_fft(fft->buf, fft->_window_size); |
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for (uint16_t i = 0; i < fft->_bin_count; i++) { |
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fft->_freq_bins[i] = std::norm(fft->buf[i]); |
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} |
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// components at the nyquist frequency are real only
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for (uint16_t i = 0, j = 0; i <= fft->_bin_count; i++, j += 2) { |
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fft->_rfft_data[j] = fft->buf[i].real(); |
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fft->_rfft_data[j+1] = fft->buf[i].imag(); |
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} |
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} |
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void DSP::mult_f32(const float* v1, const float* v2, float* vout, uint16_t len) |
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{ |
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for (uint16_t i = 0; i < len; i++) { |
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vout[i] = v1[i] * v2[i]; |
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} |
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} |
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void DSP::vector_max_float(const float* vin, uint16_t len, float* maxValue, uint16_t* maxIndex) const |
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{ |
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*maxValue = vin[0]; |
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*maxIndex = 0; |
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for (uint16_t i = 1; i < len; i++) { |
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if (vin[i] > *maxValue) { |
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*maxValue = vin[i]; |
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*maxIndex = i; |
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} |
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} |
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} |
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void DSP::vector_scale_float(const float* vin, float scale, float* vout, uint16_t len) const |
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{ |
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for (uint16_t i = 0; i < len; i++) { |
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vout[i] = vin[i] * scale; |
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} |
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} |
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// simple integer log2
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static uint16_t fft_log2(uint16_t n) |
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{ |
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uint16_t k = n, i = 0; |
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while (k) { |
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k >>= 1; |
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i++; |
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} |
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return i - 1; |
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} |
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// calculate the in-place FFT of the input using the Cooley–Tukey algorithm
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// this is a translation of Ron Nicholson's version in http://www.nicholson.com/dsp.fft1.html
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void DSP::calculate_fft(complexf *samples, uint16_t fftlen) |
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{ |
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uint16_t m = fft_log2(fftlen); |
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// shuffle data using bit reversed addressing ***
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for (uint16_t k = 0; k < fftlen; k++) { |
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// generate a bit reversed address for samples[k] ***
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uint16_t ki = k, kr = 0; |
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for (uint16_t i=1; i<=m; i++) { |
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kr <<= 1; // left shift result kr by 1 bit
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if (ki % 2 == 1) { |
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kr++; |
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} |
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ki >>= 1; // right shift temp ki by 1 bit
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} |
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// swap data samples[k] to bit reversed address samples[kr]
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if (kr > k) { |
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complexf t = samples[kr]; |
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samples[kr] = samples[k]; |
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samples[k] = t; |
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} |
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} |
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// do fft butterflys in place
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uint16_t istep = 2; |
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while (istep <= fftlen) {// layers 2,4,8,16, ... ,n
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uint16_t is2 = istep / 2; |
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uint16_t astep = fftlen / istep; |
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for (uint16_t km = 0; km < is2; km++) { // outer row loop
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uint16_t a = km * astep; // twiddle angle index
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complexf w(sinf(2 * M_PI * (a+(fftlen/4)) / fftlen), sinf(2 * M_PI * a / fftlen)); |
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for (uint16_t ki = 0; ki <= (fftlen - istep); ki += istep) { // inner column loop
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uint16_t i = km + ki; |
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uint16_t j = is2 + i; |
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complexf t = w * samples[j]; |
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complexf q = samples[i]; |
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samples[j] = q - t; |
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samples[i] = q + t; |
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} |
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} |
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istep <<= 1; |
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} |
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} |
@ -0,0 +1,55 @@
@@ -0,0 +1,55 @@
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/*
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* This file is free software: you can redistribute it and/or modify it |
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* under the terms of the GNU General Public License as published by the |
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* Free Software Foundation, either version 3 of the License, or |
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* (at your option) any later version. |
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* |
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* This file is distributed in the hope that it will be useful, but |
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* WITHOUT ANY WARRANTY; without even the implied warranty of |
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. |
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* See the GNU General Public License for more details. |
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* |
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* You should have received a copy of the GNU General Public License along |
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* with this program. If not, see <http://www.gnu.org/licenses/>.
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* |
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* Code by Andy Piper |
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*/ |
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#pragma once |
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#include <AP_HAL/AP_HAL.h> |
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#include "AP_HAL_SITL.h" |
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#include <complex> |
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typedef std::complex<float> complexf; |
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// ChibiOS implementation of FFT analysis to run on STM32 processors
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class HALSITL::DSP : public AP_HAL::DSP { |
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public: |
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// initialise an FFT instance
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virtual FFTWindowState* fft_init(uint16_t window_size, uint16_t sample_rate) override; |
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// start an FFT analysis
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virtual void fft_start(FFTWindowState* state, const float* samples, uint16_t buffer_index, uint16_t buffer_size) override; |
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// perform remaining steps of an FFT analysis
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virtual uint16_t fft_analyse(FFTWindowState* state, uint16_t start_bin, uint16_t end_bin, uint8_t harmonics, float noise_att_cutoff) override; |
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// STM32-based FFT state
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class FFTWindowStateSITL : public AP_HAL::DSP::FFTWindowState { |
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friend class HALSITL::DSP; |
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protected: |
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FFTWindowStateSITL(uint16_t window_size, uint16_t sample_rate); |
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~FFTWindowStateSITL(); |
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private: |
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complexf* buf; |
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}; |
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private: |
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void step_hanning(FFTWindowStateSITL* fft, const float* samples, uint16_t buffer_index, uint16_t buffer_size); |
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void step_fft(FFTWindowStateSITL* fft); |
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void mult_f32(const float* v1, const float* v2, float* vout, uint16_t len); |
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void vector_max_float(const float* vin, uint16_t len, float* maxValue, uint16_t* maxIndex) const override; |
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void vector_scale_float(const float* vin, float scale, float* vout, uint16_t len) const override; |
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void calculate_fft(complexf* f, uint16_t length); |
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}; |
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