Struct KalmanFilter 

pub struct KalmanFilter<const N: usize, const M: usize> {
    pub x: [f32; N],
    pub p: [[f32; N]; N],
    pub q: [[f32; N]; N],
    pub r: [[f32; M]; M],
}

Const-generic linear Kalman filter: x' = F x (+ B u) + w, z = H x + v.

Measurement dimension M must be ≤ 16 so the innovation covariance can be inverted with the crate’s stack-limited matrix inverse.

Fields

x: [f32; N]

State estimate

p: [[f32; N]; N]

State covariance P (N×N)

q: [[f32; N]; N]

Process noise covariance Q (N×N)

r: [[f32; M]; M]

Measurement noise covariance R (M×M)

Implementations

impl<const N: usize, const M: usize> KalmanFilter<N, M>

pub fn new( x0: [f32; N], p0: [[f32; N]; N], q: [[f32; N]; N], r: [[f32; M]; M], ) -> Self

Create a filter with initial state x0, covariance p0, and noise covariances q / r.

pub fn from_variances(x0: [f32; N], p_var: f32, q_var: f32, r_var: f32) -> Self

Create a filter with diagonal P, Q, and R initialized from scalar variances.

pub fn predict(&mut self, f: &[[f32; N]; N])

Prediction without control input: x ← F x, P ← F P Fᵀ + Q.

pub fn predict_with_control<const U: usize>( &mut self, f: &[[f32; N]; N], b: &[[f32; U]; N], u: &[f32; U], )

Prediction with control: x ← F x + B u, P ← F P Fᵀ + Q.

pub fn update(&mut self, h: &[[f32; N]; M], z: &[f32; M]) -> Status

Measurement update with observation matrix H (M×N) and measurement z.

On success returns Status::Success and updates x / P. If S is singular or M > 16, returns an error status and leaves the filter state unchanged.

Trait Implementations

impl<const N: usize, const M: usize> Clone for KalmanFilter<N, M>

fn clone(&self) -> KalmanFilter<N, M>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<const N: usize, const M: usize> Copy for KalmanFilter<N, M>

impl<const N: usize, const M: usize> Debug for KalmanFilter<N, M>

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

Formats the value using the given formatter.

impl<const N: usize, const M: usize> PartialEq for KalmanFilter<N, M>

fn eq(&self, other: &KalmanFilter<N, M>) -> bool

Equality operator ==.

fn ne(&self, other: &Rhs) -> bool

Inequality operator !=.

impl<const N: usize, const M: usize> StructuralPartialEq for KalmanFilter<N, M>