sunlineEKF¶

This module implements and tests a Extended Kalman Filter in order to estimate the sunline direction.

More information on can be found in the PDF Description

Functions

void SelfInit_sunlineEKF(sunlineEKFConfig *configData, int64_t moduleID)¶

This method initializes the configData for theCSS WLS estimator. It checks to ensure that the inputs are sane and then creates the output message

Return

void

Parameters

configData: The configuration data associated with the CSS WLS estimator

void CrossInit_sunlineEKF(sunlineEKFConfig *configData, int64_t moduleID)¶

This method performs the second stage of initialization for the CSS sensor interface. It’s primary function is to link the input messages that were created elsewhere.

Return

void

Parameters

configData: The configuration data associated with the CSS interface

void Reset_sunlineEKF(sunlineEKFConfig *configData, uint64_t callTime, int64_t moduleID)¶

This method resets the sunline attitude filter to an initial state and initializes the internal estimation matrices.

Return

void

Parameters

configData: The configuration data associated with the CSS estimator
callTime: The clock time at which the function was called (nanoseconds)

void Update_sunlineEKF(sunlineEKFConfig *configData, uint64_t callTime, int64_t moduleID)¶

This method takes the parsed CSS sensor data and outputs an estimate of the sun vector in the ADCS body frame

Return

void

Parameters

configData: The configuration data associated with the CSS estimator
callTime: The clock time at which the function was called (nanoseconds)

void sunlineTimeUpdate(sunlineEKFConfig *configData, double updateTime)¶

This method performs the time update for the sunline kalman filter. It calls for the updated Dynamics Matrix, as well as the new states and STM. It then updates the covariance, with process noise.

Return

void

Parameters

configData: The configuration data associated with the CSS estimator
updateTime: The time that we need to fix the filter to (seconds)

void sunlineMeasUpdate(sunlineEKFConfig *configData, double updateTime)¶

This method performs the measurement update for the sunline kalman filter. It applies the observations in the obs vectors to the current state estimate and updates the state/covariance with that information.

Return

void

Parameters

configData: The configuration data associated with the CSS estimator
updateTime: The time that we need to fix the filter to (seconds)

void sunlineStateSTMProp(double dynMat[SKF_N_STATES * SKF_N_STATES], double dt, double *stateInOut, double *stateTransition)¶

This method propagates a sunline state vector forward in time. Note that the calling parameter is updated in place to save on data copies. This also updates the STM using the dynamics matrix.

Return

void

Parameters

stateInOut

void sunlineHMatrixYMeas(double states[SKF_N_STATES], int numCSS, double cssSensorCos[MAX_N_CSS_MEAS], double sensorUseThresh, double cssNHat_B[MAX_NUM_CSS_SENSORS * 3], double CBias[MAX_NUM_CSS_SENSORS], double *obs, double *yMeas, int *numObs, double *measMat)¶

void sunlineKalmanGain(double covarBar[SKF_N_STATES * SKF_N_STATES], double hObs[MAX_N_CSS_MEAS * SKF_N_STATES], double qObsVal, int numObs, double *kalmanGain)

void sunlineDynMatrix(double stateInOut[SKF_N_STATES], double dt, double *dynMat)

This method computes the dynamics matrix, which is the derivative of the dynamics F by the state X, evaluated at the reference state. It takes in the configure data and updates this A matrix pointer called dynMat

Return

void

Parameters

states: Updated states
dt: Time step
dynMat: Pointer to the Dynamic Matrix

void sunlineCKFUpdate(double xBar[SKF_N_STATES], double kalmanGain[SKF_N_STATES * MAX_N_CSS_MEAS], double covarBar[SKF_N_STATES * SKF_N_STATES], double qObsVal, int numObs, double yObs[MAX_N_CSS_MEAS], double hObs[MAX_N_CSS_MEAS * SKF_N_STATES], double *x, double *covar)

void sunlineEKFUpdate(double kalmanGain[SKF_N_STATES * MAX_N_CSS_MEAS], double covarBar[SKF_N_STATES * SKF_N_STATES], double qObsVal, int numObs, double yObs[MAX_N_CSS_MEAS], double hObs[MAX_N_CSS_MEAS * SKF_N_STATES], double *states, double *x, double *covar)¶

struct sunlineEKFConfig¶

#include <sunlineEKF.h>

Top level structure for the CSS-based Extended Kalman Filter. Used to estimate the sun state in the vehicle body frame.

Public Members

char navStateOutMsgName[MAX_STAT_MSG_LENGTH]¶: The name of the output message

char filtDataOutMsgName[MAX_STAT_MSG_LENGTH]¶: The name of the output filter data message

char cssDataInMsgName[MAX_STAT_MSG_LENGTH]¶: The name of the Input message

char cssConfigInMsgName[MAX_STAT_MSG_LENGTH]¶: [-] The name of the CSS configuration message

double qObsVal¶: [-] CSS instrument noise parameter

double qProcVal¶: [-] Process noise parameter

double dt¶: [s] seconds since last data epoch

double timeTag¶: [s] Time tag for state/covar

double state[SKF_N_STATES]¶: [-] State estimate for time TimeTag

double x[SKF_N_STATES]¶

double xBar[SKF_N_STATES]¶: State errors

double covarBar[SKF_N_STATES * SKF_N_STATES]¶: [-] Current mean time updated state estimate [-] Time updated covariance

double covar[SKF_N_STATES * SKF_N_STATES]¶: [-] covariance

double stateTransition[SKF_N_STATES * SKF_N_STATES]¶: [-] State Transtion Matrix

double kalmanGain[SKF_N_STATES * MAX_N_CSS_MEAS]¶

double dynMat[SKF_N_STATES * SKF_N_STATES]¶: [-] Dynamics Matrix, A

double measMat[MAX_N_CSS_MEAS * SKF_N_STATES]¶: [-] Measurement Matrix H

double obs[MAX_N_CSS_MEAS]¶: [-] Observation vector for frame

double yMeas[MAX_N_CSS_MEAS]¶: [-] Linearized measurement model data

double procNoise[SKF_N_STATES / 2 * SKF_N_STATES / 2]¶: [-] process noise matrix

double measNoise[MAX_N_CSS_MEAS * MAX_N_CSS_MEAS]¶: [-] Maximally sized obs noise matrix

double postFits[MAX_N_CSS_MEAS]¶: [-] PostFit residuals

double cssNHat_B[MAX_NUM_CSS_SENSORS * 3]¶: [-] CSS normal vectors converted over to body

double CBias[MAX_NUM_CSS_SENSORS]¶: [-] CSS individual calibration coefficients

size_t numStates¶: [-] Number of states for this filter

int numObs¶: [-] Number of measurements this cycle

size_t numActiveCss¶: Number of currently active CSS sensors

size_t numCSSTotal¶: [-] Count on the number of CSS we have on the spacecraft

double sensorUseThresh¶: Threshold below which we discount sensors

double eKFSwitch¶: Max covariance element after which the filter switches to an EKF update

NavAttIntMsg outputSunline¶: Output sunline estimate data

CSSArraySensorIntMsg cssSensorInBuffer¶: [-] CSS sensor data read in from message bus

int32_t navStateOutMsgId¶: ID for the outgoing body estimate message

int32_t filtDataOutMsgId¶: [-] ID for the filter data output message

int32_t cssDataInMsgId¶: ID for the incoming CSS sensor message

int32_t cssConfigInMsgId¶: [-] ID associated with the CSS configuration data