mirror of https://github.com/ArduPilot/ardupilot
108 lines
4.6 KiB
C++
108 lines
4.6 KiB
C++
/*
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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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/*
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interface to DSP device
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*/
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#pragma once
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#include <stdint.h>
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#include "AP_HAL_Namespace.h"
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#include <AP_HAL/utility/RingBuffer.h>
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#define DSP_MEM_REGION AP_HAL::Util::MEM_FAST
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// Maximum tolerated number of cycles with missing signal
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#define FFT_MAX_MISSED_UPDATES 5
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class AP_HAL::DSP {
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#if HAL_WITH_DSP
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public:
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enum FrequencyPeak : uint8_t {
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CENTER = 0,
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LOWER_SHOULDER = 1,
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UPPER_SHOULDER = 2,
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MAX_TRACKED_PEAKS = 3,
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NONE = 4
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};
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struct FrequencyPeakData {
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// estimate of FFT peak frequency
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float _freq_hz;
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// FFT bin with maximum energy
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uint16_t _bin;
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// width of the peak
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float _noise_width_hz;
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};
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class FFTWindowState {
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public:
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// frequency width of a FFT bin
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const float _bin_resolution;
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// number of FFT bins
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const uint16_t _bin_count;
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// size of the FFT window
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const uint16_t _window_size;
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// FFT data
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float* _freq_bins;
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// derivative real data scratch space
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float* _derivative_freq_bins;
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// intermediate real FFT data
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float* _rfft_data;
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// three highest peaks
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FrequencyPeakData _peak_data[MAX_TRACKED_PEAKS];
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// Hanning window for incoming samples, see https://en.wikipedia.org/wiki/Window_function#Hann_.28Hanning.29_window
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float* _hanning_window;
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// Use in calculating the PS of the signal [Heinz] equations (20) & (21)
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float _window_scale;
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virtual ~FFTWindowState();
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FFTWindowState(uint16_t window_size, uint16_t sample_rate);
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};
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// initialise an FFT instance
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virtual FFTWindowState* fft_init(uint16_t window_size, uint16_t sample_rate) = 0;
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// start an FFT analysis with an ObjectBuffer
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virtual void fft_start(FFTWindowState* state, FloatBuffer& samples, uint16_t advance) = 0;
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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, float noise_att_cutoff) = 0;
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protected:
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// step 3: find the magnitudes of the complex data
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void step_cmplx_mag(FFTWindowState* fft, uint16_t start_bin, uint16_t end_bin, float noise_att_cutoff);
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// calculate the noise width of a peak based on the input parameters
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float find_noise_width(FFTWindowState* fft, uint16_t start_bin, uint16_t end_bin, uint16_t max_energy_bin, float cutoff, uint16_t& peak_top, uint16_t& peak_bottom) const;
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// step 4: find the bin with the highest energy and interpolate the required frequency
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uint16_t step_calc_frequencies(FFTWindowState* fft, uint16_t start_bin, uint16_t end_bin);
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// calculate a single frequency
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uint16_t calc_frequency(FFTWindowState* fft, uint16_t start_bin, uint16_t peak_bin, uint16_t end_bin);
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// find the maximum value in an vector of floats
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virtual void vector_max_float(const float* vin, uint16_t len, float* max_value, uint16_t* max_index) const = 0;
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// find the mean value in an vector of floats
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virtual float vector_mean_float(const float* vin, uint16_t len) const = 0;
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// multiple an vector of floats by a scale factor
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virtual void vector_scale_float(const float* vin, float scale, float* vout, uint16_t len) const = 0;
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// algorithm for finding peaks in noisy data as per https://terpconnect.umd.edu/~toh/spectrum/PeakFindingandMeasurement.htm
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uint16_t find_peaks(const float* input, uint16_t length, float* output, uint16_t* peaks, uint16_t peaklen,
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float slopeThreshold, float ampThreshold, uint16_t smoothwidth, uint16_t peakgroup) const;
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uint16_t val2index(const float* vector, uint16_t n, float val) const;
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void derivative(const float* input, float* output, uint16_t n) const;
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void fastsmooth(float* input, uint16_t n, uint16_t smoothwidth) const;
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// quinn's frequency interpolator
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float calculate_quinns_second_estimator(const FFTWindowState* fft, const float* complex_fft, uint16_t k) const;
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float tau(const float x) const;
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#endif // HAL_WITH_DSP
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};
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