This course introduces engineers, scientists, managers, and military personnel to the engineering of tracking sensors for air and space vehicles. Begin with a review of active and passive sensor hardware design. Focus on the accuracy of measurements needed to track, including an overview of the signal processing needed for detection, range measurement, and angle estimation. Following sensors introduction, cover optimal track filter design (Kalman filter theory). Begin with simple cases and move to combining data from multiple sensors. Address realistic problems with application of the theory, such as treatment of sensor bias and modeling errors. To conclude, briefly review tracking requirements imposed by discrimination (the fundamentals of discrimination design are addressed in other courses). The course will include examples from real radar tracking systems. Mathematical derivations will be included, but the emphasis will be on understanding the models underlying the algorithms.
- Sensor hardware design review
- Signal processing for detection, range measurement, and angle estimation
- Optimal track filter design
- Combining data from multiple sensors
- Sensor bias and modeling errors
- Review tracking requirements imposed by discrimination
- Practical real-world examples
Undergraduate degree in a technical field or equivalent experience.