/* * This file is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by the * Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This file is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. * See the GNU General Public License for more details. * * You should have received a copy of the GNU General Public License along * with this program. If not, see . * * Code by Andy Piper */ #include #if HAL_WITH_DSP #include "AP_HAL_SITL.h" #include #include #include "DSP.h" #include #include using namespace HALSITL; extern const AP_HAL::HAL& hal; // The algorithms originally came from betaflight but are now substantially modified based on theory and experiment. // https://holometer.fnal.gov/GH_FFT.pdf "Spectrum and spectral density estimation by the Discrete Fourier transform (DFT), // including a comprehensive list of window functions and some new flat-top windows." - Heinzel et. al is a great reference // for understanding the underlying theory although we do not use spectral density here since time resolution is equally // important as frequency resolution. Referred to as [Heinz] throughout the code. // initialize the FFT state machine AP_HAL::DSP::FFTWindowState* DSP::fft_init(uint16_t window_size, uint16_t sample_rate, uint8_t sliding_window_size) { DSP::FFTWindowStateSITL* fft = NEW_NOTHROW DSP::FFTWindowStateSITL(window_size, sample_rate, sliding_window_size); if (fft == nullptr || fft->_hanning_window == nullptr || fft->_rfft_data == nullptr || fft->_freq_bins == nullptr || fft->_derivative_freq_bins == nullptr) { delete fft; return nullptr; } return fft; } // start an FFT analysis void DSP::fft_start(AP_HAL::DSP::FFTWindowState* state, FloatBuffer& samples, uint16_t advance) { step_hanning((FFTWindowStateSITL*)state, samples, advance); } // perform remaining steps of an FFT analysis uint16_t DSP::fft_analyse(AP_HAL::DSP::FFTWindowState* state, uint16_t start_bin, uint16_t end_bin, float noise_att_cutoff) { FFTWindowStateSITL* fft = (FFTWindowStateSITL*)state; step_fft(fft); step_cmplx_mag(fft, start_bin, end_bin, noise_att_cutoff); return step_calc_frequencies(fft, start_bin, end_bin); } // create an instance of the FFT state machine DSP::FFTWindowStateSITL::FFTWindowStateSITL(uint16_t window_size, uint16_t sample_rate, uint8_t sliding_window_size) : AP_HAL::DSP::FFTWindowState::FFTWindowState(window_size, sample_rate, sliding_window_size) { if (_freq_bins == nullptr || _hanning_window == nullptr || _rfft_data == nullptr || _derivative_freq_bins == nullptr) { GCS_SEND_TEXT(MAV_SEVERITY_WARNING, "Failed to allocate window for DSP"); return; } buf = NEW_NOTHROW complexf[window_size]; } DSP::FFTWindowStateSITL::~FFTWindowStateSITL() { delete[] buf; } // step 1: filter the incoming samples through a Hanning window void DSP::step_hanning(FFTWindowStateSITL* fft, FloatBuffer& samples, uint16_t advance) { // 5us // apply hanning window to gyro samples and store result in _freq_bins // hanning starts and ends with 0, could be skipped for minor speed improvement uint32_t read_window = samples.peek(&fft->_freq_bins[0], fft->_window_size); if (read_window != fft->_window_size) { return; } samples.advance(advance); mult_f32(&fft->_freq_bins[0], &fft->_hanning_window[0], &fft->_freq_bins[0], fft->_window_size); } // step 2: perform an in-place FFT on the windowed data void DSP::step_fft(FFTWindowStateSITL* fft) { for (uint16_t i = 0; i < fft->_window_size; i++) { fft->buf[i] = complexf(fft->_freq_bins[i], 0); } calculate_fft(fft->buf, fft->_window_size); for (uint16_t i = 0; i < fft->_bin_count; i++) { fft->_freq_bins[i] = std::norm(fft->buf[i]); } // components at the nyquist frequency are real only for (uint16_t i = 0, j = 0; i <= fft->_bin_count; i++, j += 2) { fft->_rfft_data[j] = fft->buf[i].real(); fft->_rfft_data[j+1] = fft->buf[i].imag(); } } void DSP::mult_f32(const float* v1, const float* v2, float* vout, uint16_t len) { for (uint16_t i = 0; i < len; i++) { vout[i] = v1[i] * v2[i]; } } void DSP::vector_max_float(const float* vin, uint16_t len, float* maxValue, uint16_t* maxIndex) const { *maxValue = vin[0]; *maxIndex = 0; for (uint16_t i = 1; i < len; i++) { if (vin[i] > *maxValue) { *maxValue = vin[i]; *maxIndex = i; } } } void DSP::vector_scale_float(const float* vin, float scale, float* vout, uint16_t len) const { for (uint16_t i = 0; i < len; i++) { vout[i] = vin[i] * scale; } } void DSP::vector_add_float(const float* vin1, const float* vin2, float* vout, uint16_t len) const { for (uint16_t i = 0; i < len; i++) { vout[i] = vin1[i] + vin2[i]; } } float DSP::vector_mean_float(const float* vin, uint16_t len) const { float mean_value = 0.0f; for (uint16_t i = 0; i < len; i++) { mean_value += vin[i]; } mean_value /= len; return mean_value; } // simple integer log2 static uint16_t fft_log2(uint16_t n) { uint16_t k = n, i = 0; while (k) { k >>= 1; i++; } return i - 1; } // calculate the in-place FFT of the input using the Cooley–Tukey algorithm // this is a translation of Ron Nicholson's version in http://www.nicholson.com/dsp.fft1.html void DSP::calculate_fft(complexf *samples, uint16_t fftlen) { uint16_t m = fft_log2(fftlen); // shuffle data using bit reversed addressing *** for (uint16_t k = 0; k < fftlen; k++) { // generate a bit reversed address for samples[k] *** uint16_t ki = k, kr = 0; for (uint16_t i=1; i<=m; i++) { kr <<= 1; // left shift result kr by 1 bit if (ki % 2 == 1) { kr++; } ki >>= 1; // right shift temp ki by 1 bit } // swap data samples[k] to bit reversed address samples[kr] if (kr > k) { complexf t = samples[kr]; samples[kr] = samples[k]; samples[k] = t; } } // do fft butterflys in place uint16_t istep = 2; while (istep <= fftlen) {// layers 2,4,8,16, ... ,n uint16_t is2 = istep / 2; uint16_t astep = fftlen / istep; for (uint16_t km = 0; km < is2; km++) { // outer row loop uint16_t a = km * astep; // twiddle angle index complexf w(sinf(2 * M_PI * (a+(fftlen/4)) / fftlen), sinf(2 * M_PI * a / fftlen)); for (uint16_t ki = 0; ki <= (fftlen - istep); ki += istep) { // inner column loop uint16_t i = km + ki; uint16_t j = is2 + i; complexf t = w * samples[j]; complexf q = samples[i]; samples[j] = q - t; samples[i] = q + t; } } istep <<= 1; } } #endif