mirror of
https://github.com/hb9fxq/gr-digitalhf
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57 lines
1.5 KiB
C++
57 lines
1.5 KiB
C++
// -*- c++ -*-
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#ifndef _LIB_KALMAN_HSU_HPP_
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#define _LIB_KALMAN_HSU_HPP_
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#include <vector>
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#include "filter_update.hpp"
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#include "volk_allocator.hpp"
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namespace gr {
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namespace digitalhf {
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// see
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// [1] IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. IT-28, NO. 5, SEPTEMBER 1982 753
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// "Square Root Kalman Filtering for High-Speed Data Received over Fading Dispersive HF Channels
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// FRANK M. HSU
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// [2] https://open.library.ubc.ca/collections/ubctheses/831/items/1.0096286
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class kalman_hsu : public filter_update {
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public:
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kalman_hsu(float q, float e);
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virtual ~kalman_hsu();
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static sptr make(float q, float e);
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virtual void reset();
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virtual gr_complex const* update(gr_complex const*, gr_complex const*);
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virtual void set_parameters(std::map<std::string, float>const &);
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inline float q() const { return _q; }
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inline float e() const { return _e; }
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protected:
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void resize(size_t);
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inline unsigned idx(unsigned i, unsigned j) const {
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return i+j*(j-1)/2; // lower-triangular matrix index -> linear index
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}
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private:
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typedef std::vector<gr_complex, volk_allocator<gr_complex > > complex_vec_type;
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typedef std::vector<float, volk_allocator<float> > real_vec_type;
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float _q;
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float _e;
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complex_vec_type _g; // n -- kaman gain
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complex_vec_type _u; // n*(n-1)/2
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real_vec_type _d; // n
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real_vec_type _a; // n
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complex_vec_type _f; // n
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complex_vec_type _h; // n
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} ;
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} // namespace digitalhf
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} // namespace gr
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#endif // _LIB_KALMAN_HSU_HPP_
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