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This table provides the value of alphanumeric coded ceramic, mylar and mica capacitors in general They come in many sizes, shapes, values and ratings; many different manufacturers worldwide produce them and not all play by the same rules Some capacitors actually have the numeric values stamped on them; however, many are color coded and some have alphanumeric codes The capacitor s first and second significant number IDs are the first and second values, followed by the multiplier number code, followed by the percentage tolerance letter code Usually the first two digits of the code represent the significant part of the value, while the third digit, called the multiplier, corresponds to the number of zeros to be added to the first two digits

Answer 6-10

with Ml (0) being a zero matrix and i = l lm lq This set of simulations produces the error covariance due to each independent source of measurement noise in the absence of initial condition errors and process driving noise At the completion of the (lm + lq + lr )-th covariance simulation, each independent source of system error has been accounted for exactly once By the principle of superposition, for each k the total error covariance from all sources Pk is computed as

This is a ratio of fractions, also known as a compound fraction It s a good idea to simplify expressions like this whenever we can (as the formula above shows), because compound fractions can be awkward and confusing

(lm +lq +lr )

7

1st Significant Figure 2nd Significant Figure Multiplier Tolerance 01 F 10% CSGNetworkCom 6/4/92

Ml (k)

Question 7-1

.

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What does it mean to raise a number to the power of 2 To the power of 3 To the power of n, where n is any positive integer

104 k

Answer 7-1

Usually it is some subset of the diagonal elements of the Pk matrices that are of interest It is straightforward to tabulate the appropriate elements of Pk versus the dominant error terms (ie, M0 , Qd, R) to determine the appropriate amount that each error source must be reduced to meet a given speci cation This analysis also indicates states that are unobservable and therefore candidates for either combination or deletion Example 62 Consider the one dimensional INS system described in Example 494 on page 159 Assume that a position measurement is available at a 1 Hz rate for the rst 100 seconds of a 200-second application and that the position measurement is corrupted by white measurement noise with variance of 10 m2 A 200 second simulation of eqns (626-627) and the Kalman lter gain calculation equation results in the position error covariance illustrated in Figure 63 During the rst 100 seconds when the position aiding is available, the position covariance converges to approximately 03m2 ( p = 055m) For t [100, 200], while the aiding signal is unavailable, the position error covariance increases to approximately 3200 m2 ( p = 565m) In this simple example, we will consider three independent error sources as performance limiting factors If the present performance is not satisfactory, it is necessary to further analyze the contribution of each of the error sources to the total error covariance so that educated decisions can be made concerning which of the system components should be improved to have the greatest impact on the total system performance Figure 64 displays the results of performing separate covariance simulations for each of the following cases: 1 Total Error This simulation produces the total error depicted in Figure 63 and produces the Kalman gain sequence that will be used for the following three simulations For this simulation, R = 10m2 , Q is.

When we raise a number to the power of 2, we multiply it by itself This is also called squaring the number When we raise a number to the power of 3, we multiply it by itself, and then multiply the result by the original number again This is also called cubing the number In general, if b is any number and we raise it to the power of n, we have bn = b b b b (n times)

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