fixed typos (#147)

EKF/control.cpp

@@ -62,7 +62,7 @@ void Ekf::controlFusionModes()
 		}
 	}
 
-	// control use of various external souces for position and velocity aiding
+	// control use of various external sources for position and velocity aiding
 	controlExternalVisionAiding();
 	controlOpticalFlowAiding();
 	controlGpsAiding();
@@ -151,7 +151,7 @@ void Ekf::controlOpticalFlowAiding()
 				float range = heightAboveGndEst / _R_to_earth(2, 2);
 
 				if ((range - _params.rng_gnd_clearance) > 0.3f && _flow_sample_delayed.dt > 0.05f) {
-					// we should ahve reliable OF measurements so
+					// we should have reliable OF measurements so
 					// calculate X and Y body relative velocities from OF measurements
 					Vector3f vel_optflow_body;
 					vel_optflow_body(0) = - range * _flow_sample_delayed.flowRadXYcomp(1) / _flow_sample_delayed.dt;
@@ -183,7 +183,7 @@ void Ekf::controlOpticalFlowAiding()
 					_state.pos(0) = 0.0f;
 					_state.pos(1) = 0.0f;
 
-					// reset the coresponding covariances
+					// reset the corresponding covariances
 					// we are by definition at the origin at commencement so variances are also zeroed
 					zeroRows(P,7,8);
 					zeroCols(P,7,8);
@@ -246,7 +246,7 @@ void Ekf::controlGpsAiding()
 		// We are relying on GPS aiding to constrain attitude drift so after 10 seconds without aiding we need to do something
 		if ((_time_last_imu - _time_last_pos_fuse > 10e6) && (_time_last_imu - _time_last_vel_fuse > 10e6)) {
 			if (_time_last_imu - _time_last_gps > 5e5) {
-				// if we don't have gps then we need to switch to the non-aiding mode, zero the veloity states
+				// if we don't have gps then we need to switch to the non-aiding mode, zero the velocity states
 				// and set the synthetic GPS position to the current estimate
 				_control_status.flags.gps = false;
 				_last_known_posNE(0) = _state.pos(0);
@@ -361,7 +361,7 @@ void Ekf::controlHeightSensorTimeouts()
 			// if GPS height is unavailable and baro data is available, reset height to baro
 			reset_to_baro = reset_to_baro || (!gps_hgt_available && baro_data_fresh);
 
-			// if we cannot switch to baro and GPs data is available, reset height to GPS
+			// if we cannot switch to baro and GPS data is available, reset height to GPS
 			bool reset_to_gps = !reset_to_baro && gps_hgt_available;
 
 			if (reset_to_baro) {

EKF/covariance.cpp

@@ -53,7 +53,7 @@ void Ekf::initialiseCovariance()
 	}
 
 	// calculate average prediction time step in sec
-	float dt = 0.001f * (float)FILTER_UPDATE_PERRIOD_MS;
+	float dt = 0.001f * (float)FILTER_UPDATE_PERIOD_MS;
 
 	// define the initial angle uncertainty as variances for a rotation vector
 	Vector3f rot_vec_var;

EKF/ekf.cpp

@@ -178,7 +178,7 @@ bool Ekf::init(uint64_t timestamp)
 	_control_status.value = 0;
 	_control_status_prev.value = 0;
 
-	_dt_ekf_avg = 0.001f * (float)(FILTER_UPDATE_PERRIOD_MS);
+	_dt_ekf_avg = 0.001f * (float)(FILTER_UPDATE_PERIOD_MS);
 
 	return ret;
 }
@@ -214,7 +214,7 @@ bool Ekf::update()
 
 		// measurement updates
 
-		// Fuse magnetometer data using the selected fuson method and only if angular alignment is complete
+		// Fuse magnetometer data using the selected fusion method and only if angular alignment is complete
 		if (_mag_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_mag_sample_delayed)) {
 			if (_control_status.flags.mag_3D && _control_status.flags.yaw_align) {
 				fuseMag();
@@ -224,7 +224,7 @@ bool Ekf::update()
 				}
 
 			} else if (_control_status.flags.mag_hdg && _control_status.flags.yaw_align) {
-				// fusion of a Euler yaw angle from either a 321 or 312 rotation sequence
+				// fusion of an Euler yaw angle from either a 321 or 312 rotation sequence
 				fuseHeading();
 
 			} else {
@@ -232,7 +232,7 @@ bool Ekf::update()
 			}
 		}
 
-		// determine if range finder data has fallen behind the fusin time horizon fuse it if we are
+		// determine if range finder data has fallen behind the fusion time horizon fuse it if we are
 		// not tilted too much to use it
 		if (_range_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_range_sample_delayed)
 		    && (_R_to_earth(2, 2) > 0.7071f)) {
@@ -261,14 +261,14 @@ bool Ekf::update()
 			_fuse_height = true;
 		}
 
-		// determine if baro data has fallen behind the fuson time horizon and fuse it in the main filter if enabled
+		// determine if baro data has fallen behind the fusion time horizon and fuse it in the main filter if enabled
 		uint64_t last_baro_time_us = _baro_sample_delayed.time_us;
 		if (_baro_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_baro_sample_delayed)) {
 			if (_control_status.flags.baro_hgt) {
 				_fuse_height = true;
 
 			} else {
-				// calculate a filtered offset between the baro origin and local NED origin if we are not using the baro  as a height reference
+				// calculate a filtered offset between the baro origin and local NED origin if we are not using the baro as a height reference
 				float local_time_step = 1e-6f*(float)(_baro_sample_delayed.time_us - last_baro_time_us);
 				local_time_step = math::constrain(local_time_step,0.0f,1.0f);
 				last_baro_time_us = _baro_sample_delayed.time_us;
@@ -589,13 +589,13 @@ void Ekf::predictState()
 	float input = 0.5f*(_imu_sample_delayed.delta_vel_dt + _imu_sample_delayed.delta_ang_dt);
 
 	// filter and limit input between -50% and +100% of nominal value
-	input = math::constrain(input,0.0005f * (float)(FILTER_UPDATE_PERRIOD_MS),0.002f * (float)(FILTER_UPDATE_PERRIOD_MS));
+	input = math::constrain(input,0.0005f * (float)(FILTER_UPDATE_PERIOD_MS),0.002f * (float)(FILTER_UPDATE_PERIOD_MS));
 	_dt_ekf_avg = 0.99f * _dt_ekf_avg + 0.01f * input;
 }
 
 bool Ekf::collect_imu(imuSample &imu)
 {
-	// accumulate and downsample IMU data across a period FILTER_UPDATE_PERRIOD_MS long
+	// accumulate and downsample IMU data across a period FILTER_UPDATE_PERIOD_MS long
 
 	// copy imu data to local variables
 	_imu_sample_new.delta_ang	= imu.delta_ang;
@@ -625,7 +625,7 @@ bool Ekf::collect_imu(imuSample &imu)
 
 	// if the target time delta between filter prediction steps has been exceeded
 	// write the accumulated IMU data to the ring buffer
-	float target_dt = (float)(FILTER_UPDATE_PERRIOD_MS) / 1000;
+	float target_dt = (float)(FILTER_UPDATE_PERIOD_MS) / 1000;
 	if (_imu_down_sampled.delta_ang_dt >= target_dt - _last_dt_overrun) {
 
 		// store the amount we have over-run the target update rate by
@@ -734,7 +734,7 @@ void Ekf::calculateOutputStates()
 		delta_ang_error(2) = scalar * q_error(3);
 
 		// calculate a gain that provides tight tracking of the estimator attitude states and
-		// adjust for changes in time delay to mantain consistent damping ratio of ~0.7
+		// adjust for changes in time delay to maintain consistent damping ratio of ~0.7
 		float time_delay = 1e-6f * (float)(_imu_sample_new.time_us - _imu_sample_delayed.time_us);
 		time_delay = fmaxf(time_delay, _dt_imu_avg);
 		float att_gain = 0.5f * _dt_imu_avg / time_delay;
@@ -747,13 +747,13 @@ void Ekf::calculateOutputStates()
 		float vel_gain = _dt_ekf_avg / math::constrain(_params.vel_Tau, _dt_ekf_avg, 10.0f);
 		float pos_gain = _dt_ekf_avg / math::constrain(_params.pos_Tau, _dt_ekf_avg, 10.0f);
 
-		// calculate  velocity and position corrections at the EKF fusion time horizon
+		// calculate velocity and position corrections at the EKF fusion time horizon
 		Vector3f vel_delta = (_state.vel - _output_sample_delayed.vel) * vel_gain;
 		Vector3f pos_delta = (_state.pos - _output_sample_delayed.pos) * pos_gain;
 
 		// loop through the output filter state history and apply the corrections to the translational states
 		// this method is too expensive to use for the attitude states due to the quaternion operations required
-		// but does not introudce a time dela in the 'correction loop' and allows smaller trackin gtime constants
+		// but does not introudce a time dela in the 'correction loop' and allows smaller tracking time constants
 		// to be used
 		outputSample output_states;
 		unsigned output_length = _output_buffer.get_length();

EKF/ekf.h

@@ -159,7 +159,7 @@ private:
 	uint64_t _time_last_arsp_fuse;	// time the last fusion of airspeed measurements were performed (usec)
 	Vector2f _last_known_posNE;     // last known local NE position vector (m)
 	float _last_disarmed_posD;      // vertical position recorded at arming (m)
-	float _last_dt_overrun;		// the amount of time the last IMU collection over-ran the target set by FILTER_UPDATE_PERRIOD_MS (sec)
+	float _last_dt_overrun;		// the amount of time the last IMU collection over-ran the target set by FILTER_UPDATE_PERIOD_MS (sec)
 
 	Vector3f _earth_rate_NED;	// earth rotation vector (NED) in rad/s
 

EKF/estimator_interface.cpp

@@ -131,7 +131,7 @@ void EstimatorInterface::setMagData(uint64_t time_usec, float *data)
 		magSample mag_sample_new = {};
 		mag_sample_new.time_us = time_usec  - _params.mag_delay_ms * 1000;
 
-		mag_sample_new.time_us -= FILTER_UPDATE_PERRIOD_MS * 1000 / 2;
+		mag_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
 		_time_last_mag = time_usec;
 
 
@@ -148,7 +148,7 @@ void EstimatorInterface::setGpsData(uint64_t time_usec, struct gps_message *gps)
 		gpsSample gps_sample_new = {};
 		gps_sample_new.time_us = gps->time_usec - _params.gps_delay_ms * 1000;
 
-		gps_sample_new.time_us -= FILTER_UPDATE_PERRIOD_MS * 1000 / 2;
+		gps_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
 		_time_last_gps = time_usec;
 
 		gps_sample_new.time_us = math::max(gps_sample_new.time_us, _imu_sample_delayed.time_us);
@@ -191,7 +191,7 @@ void EstimatorInterface::setBaroData(uint64_t time_usec, float *data)
 		baro_sample_new.hgt = *data;
 		baro_sample_new.time_us = time_usec - _params.baro_delay_ms * 1000;
 
-		baro_sample_new.time_us -= FILTER_UPDATE_PERRIOD_MS * 1000 / 2;
+		baro_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
 		_time_last_baro = time_usec;
 
 		baro_sample_new.time_us = math::max(baro_sample_new.time_us, _imu_sample_delayed.time_us);
@@ -211,7 +211,7 @@ void EstimatorInterface::setAirspeedData(uint64_t time_usec, float *true_airspee
 		airspeed_sample_new.true_airspeed = *true_airspeed;
 		airspeed_sample_new.eas2tas = *eas2tas;
 		airspeed_sample_new.time_us = time_usec - _params.airspeed_delay_ms * 1000;
-		airspeed_sample_new.time_us -= FILTER_UPDATE_PERRIOD_MS * 1000 / 2; //typo PeRRiod
+		airspeed_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2; //typo PeRRiod
 		_time_last_airspeed = time_usec;
 
 		_airspeed_buffer.push(airspeed_sample_new);

EKF/estimator_interface.h

@@ -235,7 +235,7 @@ protected:
 
 	static const uint8_t OBS_BUFFER_LENGTH = 10;	// defines how many measurement samples we can buffer
 	static const uint8_t IMU_BUFFER_LENGTH = 30;	// defines how many imu samples we can buffer
-	static const unsigned FILTER_UPDATE_PERRIOD_MS = 10;	// ekf prediction period in milliseconds
+	static const unsigned FILTER_UPDATE_PERIOD_MS = 10;	// ekf prediction period in milliseconds
 
 	float _dt_imu_avg;	// average imu update period in s
 

EKF/mag_fusion.cpp

@@ -86,7 +86,7 @@ void Ekf::fuseMag()
 	float H_MAG[3][24] = {};
 	float Kfusion[24] = {};
 
-	// Calculate observation Jacobians and kalman gains for each magentoemter axis
+	// Calculate observation Jacobians and kalman gains for each magnetometer axis
 	// X Axis
 	H_MAG[0][0] = SH_MAG[7] + SH_MAG[8] - 2*magD*q2;
 	H_MAG[0][1] = SH_MAG[0];
@@ -108,7 +108,7 @@ void Ekf::fuseMag()
 		_fault_status.flags.bad_mag_x = false;
 
 	} else {
-		// the innovation variance contribution from the state covariances is negtive which means the covariance matrix is badly conditioned
+		// the innovation variance contribution from the state covariances is negative which means the covariance matrix is badly conditioned
 		_fault_status.flags.bad_mag_x = true;
 		// we need to reinitialise the covariance matrix and abort this fusion step
 		initialiseCovariance();
@@ -190,7 +190,7 @@ void Ekf::fuseMag()
 		return;
 	}
 
-	// update the states and covariance usinng sequential fusion of the magnetometer components
+	// update the states and covariance using sequential fusion of the magnetometer components
 	for (uint8_t index = 0; index <= 2; index++) {
 		// Calculate Kalman gains
 		if (index == 0) {

EKF/vel_pos_fusion.cpp

@@ -46,7 +46,7 @@
 
 void Ekf::fuseVelPosHeight()
 {
-	bool fuse_map[6] = {}; // map of booelans true when [VN,VE,VD,PN,PE,PD] observations are available
+	bool fuse_map[6] = {}; // map of booleans true when [VN,VE,VD,PN,PE,PD] observations are available
 	bool innov_check_pass_map[6] = {}; // true when innovations consistency checks pass for [VN,VE,VD,PN,PE,PD] observations
 	float R[6] = {}; // observation variances for [VN,VE,VD,PN,PE,PD]
 	float gate_size[6] = {}; // innovation consistency check gate sizes for [VN,VE,VD,PN,PE,PD] observations