Practice Advanced Tracking Algorithms (4.4) - Tracking and Resolution in Radar
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Advanced Tracking Algorithms

Practice - Advanced Tracking Algorithms

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Practice Questions

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Question 1 Easy

What is the main purpose of the Kalman Filter?

💡 Hint: Think about tracking and predictions!

Question 2 Easy

Name one limitation of the standard Kalman Filter.

💡 Hint: Consider scenarios where systems are not linear.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main function of the Kalman Filter?

To track vehicles
Optimal state estimation
Signal processing

💡 Hint: Consider what the filter's primary goal is in tracking.

Question 2

True or False: The Extended Kalman Filter is designed for use with purely linear systems.

True
False

💡 Hint: Recall what type of equations EKF deals with.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a radar tracking scenario where initial position is (0,0) with a velocity of (1,1) per time unit. The radar shows a position of (1,1) after one unit of time. If the process noise covariance is diag(0.1, 0.1) and measurement noise covariance is diag(0.2, 0.2), compute the updated position using the Kalman Filter.

💡 Hint: Remember the equations governing the Kalman Gain and update process!

Challenge 2 Hard

In a pursuit scenario, why might a Particle Filter be more effective compared to a Kalman Filter for tracking a helicopter in urban terrain when encountering obstacles?

💡 Hint: Consider how each filter handles uncertainty and non-linear behavior.

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