File syn_kalman.c¶

FileList > dsp > syn_kalman.c

General-purpose fixed-point Kalman filter implementation. More...

#include "../util/syn_assert.h"
#include "syn_kalman.h"
#include <string.h>

Public Functions¶

Type	Name
SYN_Status	syn_kalman_init (SYN_Kalman * kf, const SYN_Kalman_Config * cfg) Initialize the Kalman filter.
void	syn_kalman_predict (SYN_Kalman * kf) Predict step: propagate state and covariance forward.
SYN_Status	syn_kalman_update (SYN_Kalman * kf, const SYN_Matrix * z) Update step: incorporate a measurement.

Detailed Description¶

All operations use caller-owned SYN_Matrix instances. No heap allocation. Uses int64_t accumulator matrix multiply for full Q16 precision.

Public Functions Documentation¶

function syn_kalman_init¶

Initialize the Kalman filter.

SYN_Status syn_kalman_init (
    SYN_Kalman * kf,
    const SYN_Kalman_Config * cfg
)

The caller must have populated cfg->F, cfg->H, cfg->Q, cfg->R, and initial cfg->x and cfg->P before calling this. Scratch matrices must be assigned via SYN_KALMAN_SCRATCH_ASSIGN.

Parameters:

kf Kalman filter instance.
cfg Configuration (caller-owned, must outlive kf).

Returns:

SYN_OK on success, SYN_INVALID_PARAM on dimension mismatch.

function syn_kalman_predict¶

Predict step: propagate state and covariance forward.

void syn_kalman_predict (
    SYN_Kalman * kf
)

After this call: * x̂⁻ = F · x̂ (state predicted forward) * P⁻ = F · P · Fᵀ + Q (covariance grows)

Parameters:

kf Kalman filter instance.

function syn_kalman_update¶

Update step: incorporate a measurement.

SYN_Status syn_kalman_update (
    SYN_Kalman * kf,
    const SYN_Matrix * z
)

After this call: * x̂ is corrected toward the measurement * P is reduced (uncertainty decreased)

Parameters:

kf Kalman filter instance.
z Measurement vector (n_meas × 1).

Returns:

SYN_OK on success, SYN_ERROR if innovation covariance is singular.

The documentation for this class was generated from the following file src/syntropic/dsp/syn_kalman.c