Struct ExtendedKalmanFilter 

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

Extended Kalman filter with compile-time dimensions and a user EkfModel.

Measurement dimension M must be ≤ 16. Covariance update uses P ← (I − KH) P.

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)

model: Model

Nonlinear process / measurement model

Implementations

impl<const N: usize, const M: usize, Model: EkfModel<N, M>> ExtendedKalmanFilter<N, M, Model>

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

Create an EKF with initial state, covariances, and model.

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

Create an EKF with diagonal covariances from scalar variances.

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

EKF predict: x ← f(x, dt), P ← F P Fᵀ + Q with F = ∂f/∂x.

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

EKF update with measurement z. Linearizes h at the current estimate.

On singular innovation covariance or M > 16, returns an error and leaves state unchanged.

Trait Implementations

impl<const N: usize, const M: usize, Model: Clone> Clone for ExtendedKalmanFilter<N, M, Model>

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

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, Model: Copy> Copy for ExtendedKalmanFilter<N, M, Model>

impl<const N: usize, const M: usize, Model: Debug> Debug for ExtendedKalmanFilter<N, M, Model>

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

Formats the value using the given formatter.

impl<const N: usize, const M: usize, Model: PartialEq> PartialEq for ExtendedKalmanFilter<N, M, Model>

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

Equality operator ==.

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

Inequality operator !=.

impl<const N: usize, const M: usize, Model: PartialEq> StructuralPartialEq for ExtendedKalmanFilter<N, M, Model>