kopia lustrzana https://github.com/f4exb/sdrangel
137 wiersze
3.1 KiB
C++
137 wiersze
3.1 KiB
C++
// Copyright 2021 Rob Riggs <rob@mobilinkd.com>
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// All rights reserved.
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#pragma once
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#include "IirFilter.h"
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#include <algorithm>
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#include <array>
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#include <cmath>
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#include <cstddef>
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#include "export.h"
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namespace modemm17 {
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/**
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* Deviation and zero-offset estimator.
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*
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* Accepts samples which are periodically used to update estimates of the
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* input signal deviation and zero offset.
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*
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* Samples must be provided at the ideal sample point (the point with the
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* peak bit energy).
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*
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* Estimates are expected to be updated at each sync word. But they can
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* be updated more frequently, such as during the preamble.
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*/
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class MODEMM17_API FreqDevEstimator
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{
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public:
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using sample_filter_t = BaseIirFilter<3>;
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void reset()
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{
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min_est_ = 0.0f;
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max_est_ = 0.0f;
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min_var_ = 0.0f;
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max_var_ = 0.0f;
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min_count_ = 0;
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max_count_ = 0;
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min_cutoff_ = 0.0f;
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max_cutoff_ = 0.0f;
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}
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void sample(float sample)
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{
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if (sample < 1.5 * min_est_)
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{
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min_count_ = 1;
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min_est_ = sample;
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min_var_ = 0.0f;
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min_cutoff_ = min_est_ * 0.666666f;
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}
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else if (sample < min_cutoff_)
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{
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min_count_ += 1;
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min_est_ += sample;
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float var = (min_est_ / min_count_) - sample;
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min_var_ += var * var;
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}
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else if (sample > 1.5f * max_est_)
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{
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max_count_ = 1;
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max_est_ = sample;
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max_var_ = 0.0f;
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max_cutoff_ = max_est_ * 0.666666f;
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}
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else if (sample > max_cutoff_)
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{
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max_count_ += 1;
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max_est_ += sample;
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float var = (max_est_ / max_count_) - sample;
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max_var_ += var * var;
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}
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}
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/**
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* Update the estimates for deviation, offset, and EVM (error). Note
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* that the estimates for error are using a sloppy implementation for
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* calculating variance to reduce the memory requirements. This is
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* because this is designed for embedded use.
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*/
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void update()
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{
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if (max_count_ < 2 || min_count_ < 2) {
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return;
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}
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float max_ = max_est_ / max_count_;
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float min_ = min_est_ / min_count_;
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deviation_ = (max_ - min_) / 6.0;
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offset_ = dc_filter_(std::max(std::min(max_ + min_, deviation_ * MAX_DC_ERROR), deviation_ * -MAX_DC_ERROR));
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error_ = (std::sqrt(max_var_ / (max_count_ - 1)) + std::sqrt(min_var_ / (min_count_ - 1))) * 0.5;
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if (deviation_ > 0) {
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idev_ = 1.0 / deviation_;
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}
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min_cutoff_ = offset_ - deviation_ * 2;
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max_cutoff_ = offset_ + deviation_ * 2;
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max_est_ = max_;
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min_est_ = min_;
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max_count_ = 1;
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min_count_ = 1;
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max_var_ = 0.0f;
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min_var_ = 0.0f;
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}
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float deviation() const { return deviation_; }
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float offset() const { return offset_; }
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float error() const { return error_; }
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float idev() const { return idev_; }
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private:
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// IIR with Nyquist of 1/4.
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static const std::array<float, 3> dc_b;
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static const std::array<float, 3> dc_a;
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static const float MAX_DC_ERROR;
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float min_est_ = 0.0f;
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float max_est_ = 0.0f;
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float min_cutoff_ = 0.0f;
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float max_cutoff_ = 0.0f;
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float min_var_ = 0.0f;
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float max_var_ = 0.0f;
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size_t min_count_ = 0;
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size_t max_count_ = 0;
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float deviation_ = 0.0f;
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float offset_ = 0.0f;
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float error_ = 0.0f;
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float idev_ = 1.0f;
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sample_filter_t dc_filter_{dc_b, dc_a};
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};
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} // modemm17
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