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The NPN Case The normal method of biasing an NPN transistor is to have the collector voltage positive with respect to the emitter This is shown by the connection of the battery in Figs 22-3A and 22-3B Typical dc voltages for a transistor power supply range between 3 V and about 50 V A typical voltage is 12 V In the model and also in the real-world transistor circuit, the base is labeled control, because the flow of current through the transistor depends critically on what happens at this electrode Zero Bias for NPN Suppose the base of a transistor is at the same voltage as the emitter This is known as zero bias When the forward bias is zero, the emitter-base current, often called simply base current and de-

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(1066)

Using either approach of Section 103, the initial values for the quaternion b(t2 ), the gyro errors xg (t2 ), and the accelerometer errors xa (t2 ) can be de ned from the sensor data Given these initial conditions, the mechanization equations of Section 104 would be integrated through time to provide the reference trajectory b(t) for t > t2 In addition, at any time t that they are required, the quaternion can be used to compute values for either

noted IB, is zero, and the emitter-base (E-B) junction does not conduct This prevents current from flowing between the emitter and collector, unless a signal is injected at the base to change the situation Such a signal must, at least momentarily, attain a positive voltage equal to or greater than the forward breakover voltage of the E-B junction

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the Euler angles ( (t), (t), (t)) or the rotation matrices Rb (t) and Rn (t) n b The aiding with magnetometer measurements can be accomplished at a designer speci ed periodic rate The aiding via the accelerometer measurements will be performed asynchronously at selected time instants where the acceleration vector is deemed to be small as discussed in Section 1054 If the symbol tk for k = 1, 2, 3, is used to indicate times at which Kalman lter corrections occur, then the error covariance matrix is propagated between these time instants according to P = (tk , tk 1 )P+ (tk , tk 1 ) + Qdk 1 k k 1 Because the accelerometer measurements are asynchronous, the matrices and Qdk must be computed online For t [tk 1 , tk ] the state transition matrix (t, tk 1 ) is accumulated as described in eqn (720) and the discrete-time process noise matrix Qdk is accumulated as described in eqn (721) The integration of the state transition matrix and the discrete-time process noise matrix are initiated at tk 1 according to: (tk 1 , tk 1 ) = I and Q(tk 1 , tk 1 ) = 0 xk At time tk , the Kalman gain Kk , the state correction + , and the error covariance of matrix P+ , are each computed using the standard Kalman k lter equations With + available, it is necessary to initialize the state xk vector for the next period of integration The accelerometer and gyro bias states are straightforward: xa (tk )+ xg (tk )+ = xa (tk ) + a (tk )+ x = xg (tk ) + g (tk )+ x

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The rst three components of x+ de ne + (tk ), according to eqn (1031) k the corrected rotation matrix is Rb (tk ) n

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