Add typedef for Matrix 24 types

EKF/airspeed_fusion.cpp

@@ -172,7 +172,7 @@ void Ekf::fuseAirspeed()
 		// apply covariance correction via P_new = (I -K*H)*P
 		// first calculate expression for KHP
 		// then calculate P - KHP
-		matrix::SquareMatrix<float, _k_num_states> KHP;
+		SquareMatrix24f KHP;
 		float KH[5];
 
 		for (unsigned row = 0; row < _k_num_states; row++) {

EKF/covariance.cpp

@@ -218,7 +218,7 @@ void Ekf::predictCovariance()
 	}
 
 	// compute noise variance for stationary processes
-	matrix::Vector<float, _k_num_states> process_noise;
+	Vector24f process_noise;
 
 	// Construct the process noise variance diagonal for those states with a stationary process model
 	// These are kinematic states and their error growth is controlled separately by the IMU noise variances
@@ -328,7 +328,7 @@ void Ekf::predictCovariance()
 	SPP[10] = SF[16];
 
 	// covariance update
-	matrix::SquareMatrix<float, _k_num_states> nextP;
+	SquareMatrix24f nextP;
 
 	// calculate variances and upper diagonal covariances for quaternion, velocity, position and gyro bias states
 	nextP(0,0) = P(0,0) + P(1,0)*SF[9] + P(2,0)*SF[11] + P(3,0)*SF[10] + P(10,0)*SF[14] + P(11,0)*SF[15] + P(12,0)*SPP[10] + (daxVar*SQ[10])/4 + SF[9]*(P(0,1) + P(1,1)*SF[9] + P(2,1)*SF[11] + P(3,1)*SF[10] + P(10,1)*SF[14] + P(11,1)*SF[15] + P(12,1)*SPP[10]) + SF[11]*(P(0,2) + P(1,2)*SF[9] + P(2,2)*SF[11] + P(3,2)*SF[10] + P(10,2)*SF[14] + P(11,2)*SF[15] + P(12,2)*SPP[10]) + SF[10]*(P(0,3) + P(1,3)*SF[9] + P(2,3)*SF[11] + P(3,3)*SF[10] + P(10,3)*SF[14] + P(11,3)*SF[15] + P(12,3)*SPP[10]) + SF[14]*(P(0,10) + P(1,10)*SF[9] + P(2,10)*SF[11] + P(3,10)*SF[10] + P(10,10)*SF[14] + P(11,10)*SF[15] + P(12,10)*SPP[10]) + SF[15]*(P(0,11) + P(1,11)*SF[9] + P(2,11)*SF[11] + P(3,11)*SF[10] + P(10,11)*SF[14] + P(11,11)*SF[15] + P(12,11)*SPP[10]) + SPP[10]*(P(0,12) + P(1,12)*SF[9] + P(2,12)*SF[11] + P(3,12)*SF[10] + P(10,12)*SF[14] + P(11,12)*SF[15] + P(12,12)*SPP[10]) + (dayVar*sq(q2))/4 + (dazVar*sq(q3))/4;

EKF/drag_fusion.cpp

@@ -241,7 +241,7 @@ void Ekf::fuseDrag()
 			// apply covariance correction via P_new = (I -K*H)*P
 			// first calculate expression for KHP
 			// then calculate P - KHP
-			matrix::SquareMatrix<float, _k_num_states> KHP;
+			SquareMatrix24f KHP;
 			float KH[9];
 
 			for (unsigned row = 0; row < _k_num_states; row++) {

EKF/ekf.h

@@ -47,6 +47,9 @@
 class Ekf : public EstimatorInterface
 {
 public:
+	static constexpr uint8_t _k_num_states{24};		///< number of EKF states
+	typedef matrix::Vector<float, _k_num_states> Vector24f;
+	typedef matrix::SquareMatrix<float, _k_num_states> SquareMatrix24f;
 
 	Ekf() = default;
 	virtual ~Ekf() = default;
@@ -297,9 +300,6 @@ public:
 	void requestEmergencyNavReset() override;
 
 private:
-
-	static constexpr uint8_t _k_num_states{24};		///< number of EKF states
-
 	struct {
 		uint8_t velNE_counter;	///< number of horizontal position reset events (allow to wrap if count exceeds 255)
 		uint8_t velD_counter;	///< number of vertical velocity reset events (allow to wrap if count exceeds 255)
@@ -382,7 +382,7 @@ private:
 
 	bool _yaw_use_inhibit{false};		///< true when yaw sensor use is being inhibited
 
-	matrix::SquareMatrix<float, _k_num_states> P;	///< state covariance matrix
+	SquareMatrix24f P;	///< state covariance matrix
 
 	Vector3f _delta_vel_bias_var_accum;		///< kahan summation algorithm accumulator for delta velocity bias variance
 	Vector3f _delta_angle_bias_var_accum;	///< kahan summation algorithm accumulator for delta angle bias variance

EKF/gps_yaw_fusion.cpp

@@ -218,7 +218,7 @@ void Ekf::fuseGpsAntYaw()
 	// apply covariance correction via P_new = (I -K*H)*P
 	// first calculate expression for KHP
 	// then calculate P - KHP
-	matrix::SquareMatrix<float, _k_num_states> KHP;
+	SquareMatrix24f KHP;
 	float KH[4];
 
 	for (unsigned row = 0; row < _k_num_states; row++) {

EKF/mag_fusion.cpp

@@ -355,7 +355,7 @@ void Ekf::fuseMag()
 		// apply covariance correction via P_new = (I -K*H)*P
 		// first calculate expression for KHP
 		// then calculate P - KHP
-		matrix::SquareMatrix<float, _k_num_states> KHP {};
+		SquareMatrix24f KHP;
 		float KH[10];
 
 		for (unsigned row = 0; row < _k_num_states; row++) {
@@ -705,7 +705,7 @@ void Ekf::updateQuaternion(const float innovation, const float variance, const f
 	// apply covariance correction via P_new = (I -K*H)*P
 	// first calculate expression for KHP
 	// then calculate P - KHP
-	matrix::SquareMatrix<float, _k_num_states> KHP;
+	SquareMatrix24f KHP;
 	float KH[4];
 
 	for (unsigned row = 0; row < _k_num_states; row++) {
@@ -995,7 +995,7 @@ void Ekf::fuseDeclination(float decl_sigma)
 	// first calculate expression for KHP
 	// then calculate P - KHP
 	// take advantage of the empty columns in KH to reduce the number of operations
-	matrix::SquareMatrix<float, _k_num_states> KHP;
+	SquareMatrix24f KHP;
 	float KH[2];
 	for (unsigned row = 0; row < _k_num_states; row++) {
 

EKF/optflow_fusion.cpp

@@ -440,7 +440,7 @@ void Ekf::fuseOptFlow()
 		// apply covariance correction via P_new = (I -K*H)*P
 		// first calculate expression for KHP
 		// then calculate P - KHP
-		matrix::SquareMatrix<float, _k_num_states> KHP;
+		SquareMatrix24f KHP;
 		float KH[7];
 
 		for (unsigned row = 0; row < _k_num_states; row++) {

EKF/sideslip_fusion.cpp

@@ -214,7 +214,7 @@ void Ekf::fuseSideslip()
 		// apply covariance correction via P_new = (I -K*H)*P
 		// first calculate expression for KHP
 		// then calculate P - KHP
-		matrix::SquareMatrix<float, _k_num_states> KHP;
+		SquareMatrix24f KHP;
 		float KH[9];
 
 		for (unsigned row = 0; row < _k_num_states; row++) {

EKF/vel_pos_fusion.cpp

@@ -161,7 +161,7 @@ void Ekf::fuseVelPosHeight(const float innov, const float innov_var, const int o
 		Kfusion[row] = P(row, state_index) / innov_var;
 	}
 
-	matrix::SquareMatrix<float, _k_num_states> KHP;
+	SquareMatrix24f KHP;
 
 	for (unsigned row = 0; row < _k_num_states; row++) {
 		for (unsigned column = 0; column < _k_num_states; column++) {