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R3 22k ohm 1 4 watt, / 5% resistor (red-red-gold) / R4 1 ohm 1 2 watt, 5% resistor (brown-black-gold) R5 C1 10 ohm 10 watt, 10% resistor 10 f, 25 volt electrolytic capacitor

If the gain sequence Lk is known, then eqns (4125 4127) can be iterated to quantify the expected accuracy of the state estimation design for the given Lk Eqn (4127) is true for any state feedback gain Lk ; therefore, this equation allows the performance (as measured by state error covariance) of alternative gain sequences to be quantitatively compared In fact, eqn (4127) expresses the covariance of the state estimate immediately after the measurement correction as a function of the estimation gain vector Lk ; therefore, a new gain vector could be selected at each time instant to minimize the state estimation error variance This is the topic of optimal stochastic state estimation which is discussed in 5

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The identity element You can multiply or divide any integer by 1, and it won t change the value Because multiplying or dividing by 1 always gives you the same number again, 1 is called the multiplicative identity element (For some reason I ve never heard it called the divisive identity element, but technically this term is okay) For any integer a

This section presents a few detailed examples intended to demonstrate the utility of random variables and stochastic processes in relation to navigation applications Sections 491 and 492 focus on frequently asked questions Sections 493 and 494 discuss navigation examples that are relatively simple compared to those in Part II of the book, but follow the same methodology

The sign-changing element When you multiply or divide any integer by 1, you reverse the sign but do not change the absolute value A positive integer becomes negative, and a negative integer becomes positive, but the distance from 0 on the integer line stays the same For any integer a

C3,C7 1 F, 35 volt disk capacitor C4 C5 C6 47 nF, 35 volt poly capacitor 10 F, 35 volt electrolytic capacitor 220 F, 35 volt electrolytic capacitor

a( 1) = a and a/( 1) = a Conversely, a( 1) = a and a/( 1) = a Note that a( 1) here means a times 1, not a minus 1 Those parentheses are important! The integer 1 can be called the multiplicative sign-changing element or the divisive sign-changing element

Various terms are used to characterize navigation system performance This section uses results from linear algebra, properties of Gaussian random variables, and the change of variable concepts from Section 434, to derive the relationships between these alternative performance characterizations The discussion makes two basic assumptions: 1 The position error vector w = [n, e, d] able is a Gaussian random vari-

Parentheses in simple products and quotients Look at these expressions:

2 The components of the position error are unbiased The validity of the assumptions must be considered in the use of the subsequent results The Normal (Gaussian) assumption is motivated by the Central Limit Theorem Although the assumption may not be absolutely valid, the large number of small, independent error sources in a navigation system results in error distributions which can be accurately approximated as Gaussian This assumption is not typically a major source of di culty The unbiased assumption must be considered more carefully The unbiased assumption can be considered as a distinction between precision and accuracy Ideally, an analyst would calculate errors as x = x x where

3 ( 5) = a and 15/( 3) = b If you don t write the parentheses, the above expressions are 3 5 = a and 15/ 3 = b Expressions like these might be clear enough to you, but they would confuse some people Don t be afraid to add parentheses to an expression if you think they will prevent ambiguity Just be sure that for every opening parenthesis you put in, you include a corresponding closing parenthesis later in the expression

C2,C5 100 nF, 35 volt poly capacitor C3 100 F, 35 volt electrolytic capacitor C4 470 F, 35 volt electrolytic capacitor

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