Struct KalmanFilter1D 

pub struct KalmanFilter1D {
    pub x: f32,
    pub p: f32,
    pub q: f32,
    pub r: f32,
}

1D scalar Kalman filter for sensor fusion and signal smoothing.

State: x̂ (estimate), P (estimate covariance) Model: x_k = x_{k-1} + process_noise y_k = x_k + measurement_noise

Fields

x: f32

Estimated state.

p: f32

Estimate error covariance.

q: f32

Process noise covariance Q.

r: f32

Measurement noise covariance R.

Implementations

impl KalmanFilter1D

pub fn new(initial_estimate: f32, q: f32, r: f32) -> Self

Create a new filter.

• initial_estimate — initial state estimate
• q — process noise variance (larger = more responsive)
• r — measurement noise variance (larger = more smoothing)

pub fn predict(&mut self, _dt: f32)

Predict step (constant-velocity model here: x = x, P = P + Q).

pub fn update(&mut self, measurement: f32)

Update with a new measurement.

pub fn filter(&mut self, measurement: f32, dt: f32) -> f32

Predict then update in one step.

pub fn estimate(&self) -> f32

Current estimate.

pub fn filter_buffer(&mut self, measurements: &[f32], dt: f32) -> Vec<f32>

Filter a buffer of measurements.

pub fn reset(&mut self, initial: f32)

Reset to a new initial state.

Trait Implementations

impl Clone for KalmanFilter1D

fn clone(&self) -> KalmanFilter1D

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for KalmanFilter1D

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.