%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%*/
#include "FGFCSComponent.h"
-#include <input_output/FGXMLElement.h>
+#include <string>
/*%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
DEFINITIONS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%*/
-#define ID_SENSOR "$Id$"
+#define ID_SENSOR "$Id: FGSensor.h,v 1.21 2012/01/08 12:39:14 bcoconni Exp $"
/*%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
FORWARD DECLARATIONS
namespace JSBSim {
class FGFCS;
+class Element;
/*%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
CLASS DOCUMENTATION
<sensor name="name">
<input> property </input>
<lag> number </lag>
- <noise variation="PERCENT|ABSOLUTE"> number </noise>
+ <noise [variation="PERCENT|ABSOLUTE"] [distribution="UNIFORM|GAUSSIAN"]> number </noise>
<quantization name="name">
<bits> number </bits>
<min> number </min>
<max> number </max>
</quantization>
<drift_rate> number </drift_rate>
+ <gain> number </gain>
<bias> number </bias>
+ <delay> number < /delay>
</sensor>
@endcode
The only required element in the sensor definition is the input element. In that
case, no degradation would be modeled, and the output would simply be the input.
-For noise, if the type is PERCENT, then the value supplied is understood to be a
-percentage variance. That is, if the number given is 0.05, the the variance is
-understood to be +/-0.05 percent maximum variance. So, the actual value for the sensor
-will be *anywhere* from 0.95 to 1.05 of the actual "perfect" value at any time -
-even varying all the way from 0.95 to 1.05 in adjacent frames - whatever the delta
-time.
+Noise can be Gaussian or uniform, and the noise can be applied as a factor (PERCENT)
+or additively (ABSOLUTE). The noise that can be applied at each frame of the
+simulation execution is calculated as a random factor times a noise value that
+is specified in the config file. When the noise distribution type is Gaussian,
+the random number can be between roughly -3 and +3 for a span of six sigma. When
+the distribution type is UNIFORM, the random value can be between -1.0 and +1.0.
+This random value is multiplied against the specified noise to arrive at a random
+noise value for the frame. If the noise type is PERCENT, then random noise value
+is added to one, and that sum is then multiplied against the input signal for the
+sensor. In this case, the specified noise value in the config file would be
+expected to actually be a percent value, such as 0.05 (for a 5% variance). If the
+noise type is ABSOLUTE, then the random noise value specified in the config file
+is understood to be an absolute value of noise to be added to the input signal
+instead of being added to 1.0 and having that sum be multiplied against the input
+signal as in the PERCENT type. For the ABSOLUTE noise case, the noise number
+specified in the config file could be any number.
+
+If the type is ABSOLUTE, then the noise number times the random number is
+added to the input signal instead of being multiplied against it as with the
+PERCENT type of noise.
+
+The delay element can specify a frame delay. The integer number provided is
+the number of frames to delay the output signal.
@author Jon S. Berndt
-@version $Revision$
+@version $Revision: 1.21 $
*/
/*%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
{
public:
FGSensor(FGFCS* fcs, Element* element);
- ~FGSensor();
+ virtual ~FGSensor();
void SetFailLow(double val) {if (val > 0.0) fail_low = true; else fail_low = false;}
void SetFailHigh(double val) {if (val > 0.0) fail_high = true; else fail_high = false;}
protected:
enum eNoiseType {ePercent=0, eAbsolute} NoiseType;
- double dt;
+ enum eDistributionType {eUniform=0, eGaussian} DistributionType;
double min, max;
double span;
double bias;
+ double gain;
double drift_rate;
double drift;
double noise_variance;
bool fail_low;
bool fail_high;
bool fail_stuck;
- string quant_property;
+ std::string quant_property;
+ void ProcessSensorSignal(void);
void Noise(void);
void Bias(void);
void Drift(void);
void Quantize(void);
void Lag(void);
+ void Gain(void);
void bind(void);