Documentation ¶
Index ¶
Constants ¶
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Variables ¶
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Functions ¶
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Types ¶
type Context ¶
type Context struct { X *mat.VecDense // Current system state P *mat.Dense // Current covariance matrix }
Context contains the current state and covariance of the system
type Filter ¶
type Filter interface { Apply(ctx *Context, z, ctrl *mat.VecDense) mat.Vector CurrentState() mat.Vector PredictState(ctx *Context, ctrl *mat.VecDense) *mat.VecDense }
Filter interface for using the Kalman filter
func NewRoseFilter ¶
NewRoseFilter returns a ROSE Kalman filter Rapid Ongoing Stochasic covariance Estimation (ROSE) Filter lti: discrete linear, time-invariante system Gd: discretized G matrix for system noise gammaR: Gain factor for measurement noise alphaR: Kalman gain for measurment covariance noise alphaM: Kalman gain for covariance M
type Noise ¶
Noise represents the measurement and system noise
func NewZeroNoise ¶
NewZeroNoise initializes a Noise struct q: dimension of square matrix Q r: dimension of square matrix R
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