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CHAPTER 5 OPTIMAL STATE ESTIMATION O -line Calculations x(t) = f ( (t), u(t), t) x yk = h( k , k) x f F( (t), u(t), t) = x x= x x

Part One Question 3-7

h x x(tk )= (tk ) x 1 Kk = P Hk Rk + Hk P Hk k k + Pk = [I Kk Hk ]Pk P = k P+ k + Qdk k+1 k

Answer 3-7

locate a clean well lit and well ventilated work area A large table or workbench would be a suitable work surface for your project Next you will want to locate a small 27 to 33 watt pencil-tipped soldering iron, as well as a roll of #22 ga 60/40 tin/lead solder and a small jar

0 x = x0 P = var( x ) 0 0 zk = yk yk + = + Kk zk Hk xk xk xk = k + xk+1 xk

A perfect square is the result of multiplying a natural number by itself The first few perfect squares are 0, 1, 4, 9, 16, 25, 36, 49, and 64 No perfect square can be prime By definition, 0 and 1 are not prime Any perfect square larger than 1 can be broken down into a product of two or more primes, so it s composite

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Table 57: Linearized Kalman lter equations Computation of the matrices k and Qdk is discussed in Section 471 su ciently accurate, then 1) the state estimate should be near the actual state; 2) the linearization should be accurate; and, 3) the performance should be good If however, the estimate is far from the actual state, the linearization will be inaccurate and the estimate may diverge rapidly The possibility of using a poor state estimate in the lter gain calculations makes the Extended Kalman Filter (EKF) riskier than the linearized Kalman lter Alternatively, the fact that the estimated state is typically (under good observability conditions) closer to the actual state than a prede ned nominal trajectory usually allows the extended Kalman lter to produce better performance than the linearized Kalman lter The implementation equations for the EKF are summarized in Table 58 The algorithm can be manipulated to correctly work with either total states (ie, x(t)) or error states (ie, (t)), as discussed further in Section x 51053 51053 Complementary Filtering and the EKF

Question 3-8

of Tip Tinner, a soldering iron tip cleaner/dresser from your local Radio Shack store You will also want to secure a few hand tools for the project, such as a pair of small end-cutters, a pair of tweezers and a pair of needle-nose pliers Locate a small Phillips and a small flat-blade screwdriver, as well as a magnifying glass to round out your tool list Grab the schematic, parts layout diagram as well as the resistor and capacitor identifier charts and we will begin our project Place all the project components on the table in front of you The ultra-low frequency receiver is an RF or radio frequency project and it is best constructed on a printed circuit board with large ground plane areas covering the board for the best RF grounding techniques Once you have all the parts and PC board in front of you, heat up the soldering iron and we ll get started! First, find your resistor identifier chart in Table 21-1, which will help you select the resistors from the parts pile Resistors used in this project are mostly small 1 4 watt carbon composition type resistors, which have colored bands along the resistor body The first color band should be closest to one end of the resistor body This first color band represents the first digit of the resistor value For example, resistor R5, R6 and R10 has four color bands, the first one is a brown band followed by a black band followed by an orange band The fourth band is gold The first band is brown which denotes a

How can we write down the set Z of integers as an implied, two-ended list As an implied, one-ended list

In the implementation of the EKF, the solution to k x x (t) = f ( (t), u(t), t), for t [tk , tk+1 ) with x (tk ) = x+ is required between sampling instants This book will primarily focus on navigation systems implemented using a complementary lter structure,

Answer 3-8

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