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Estimation Theory Final Test

December 8, 2010

1. A simplified spacecraft tracking problem is formulated by

c c c

c c c c

x w , w ~N(0, )

z x v , v ~N(0, q r

=

= +

).

)

(T10.2.1-1)

(a) Suppose that the measurements are taken every 0.5 second. Show that the discrete model for Eq. (T10.2.1-1) is given by

( 1) ( ) (

( ) ( ) ( ).

x k x k w

z k x k v k + = +

= +

k (T10.2.1-2)

Determine the mean and variance of w k( ) and v k( ).

(b) Find the steady-state Kalman filter solution for this problem assuming that and are white Gaussian and uncorrelated each other.

( )

w k v k( )

(c) Find the causal Wiener filter solution for this problem and compare it with the result of (b).

(d) Find the steady-state optimal smooth solution for this problem and compare it with the result of (b).

(For (b), (c), and (d), let q= =r 1.)

2. Consider the following state and measurement equations

k k

k x w

x ⎥ +

⎢ ⎤

=⎡

+ 0 1

0 4

1 , ⎟⎟⎠,

⎜⎜⎝

⎛ ⎥

⎢ ⎤

⎡ 5 . 0 0

0 , 0 0

k ~

w x0 ~

(

0,P0

)

k k

k Hx v

z = + , vk ~

( )

0,1 .

1

(2)

(a) Determine if the steady-state Kalman gain K is asymptotically stable when

[

0 3

]

H = .

(b) What if H =

[

3 3

]

?

3. The equation of motion of a pendulum hanging from a ceiling is given by the differential equation

2 2

( ) sin ( ) ( ), d t

t w t dt

θ + θ =

where is the angular position of the pendulum at time t. Discrete measurements of are given by , where the sampling

interval . Suppose that , , and

. Give the equations for the EKF that provides an estimate of

, , based on the measurements for . ( )t

θ

T (0, N

=1,2

( )t

θ z n( )=θ( )n +v n( ) ( ) ~ (0, 0.02) w t N

( )

z i =

=0.5 0.02)

,"

( ) ~ (0,1) v n N

1,2, ,

i " n

(0) ~ θ

( )i

θ i

4. Suppose that RV x is uniformly distributed on [-1, 1], and y=e2x. (a) What is the mean of y, y?

(b) What is the first-order approximation to y?

(c) What is the second-order approximation to y?

(d) What is the unscented approximation to y?

(e) What is the variance of y? What is the unscented approximation to the variance of y?

2

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