## ELEC ENG 7002 - Kalman Filtering & Applications

### North Terrace Campus - Semester 1 - 2021

The Kalman Filter: Stochastic state-variable systems; Optimality criteria for the estimation of state variables; The maximum-likelihood solution for independent Gaussian noise processes; The innovations sequence; The least-squares Kalman filter; Systems with correlated noise processes; Stochastic systems with time-invariant coefficients; The square-root algorithm; The extended Kalman filter, Adaptive system identification.

• General Course Information
##### Course Details
Course Code ELEC ENG 7002 Kalman Filtering & Applications School of Electrical & Electronic Engineering Semester 1 Postgraduate Coursework North Terrace Campus 3 Up to 42 hours Y Linear algebra (matrices), probability theory, linear systems & MATLAB The Kalman Filter: Stochastic state-variable systems; Optimality criteria for the estimation of state variables; The maximum-likelihood solution for independent Gaussian noise processes; The innovations sequence; The least-squares Kalman filter; Systems with correlated noise processes; Stochastic systems with time-invariant coefficients; The square-root algorithm; The extended Kalman filter, Adaptive system identification.
##### Course Staff

Course Coordinator: Professor Peng Shi

Email: peng.shi@adelaide.edu.au
Phone: 8313 6424
##### Course Timetable

The full timetable of all activities for this course can be accessed from Course Planner.

• Learning Outcomes
##### Course Learning Outcomes
On successful completion of this course students will be able to:

 1 Explain fundamental principles of Kalman filtering 2 Describe the properties and structure of Kalman filter 3 Design Kalman filters for simple practical cases 4 Discuss basic target tracking theory and its applications.

The above course learning outcomes are aligned with the Engineers Australia Stage 1 Competency Standard for the Professional Engineer.
The course is designed to develop the following Elements of Competency: 1.1   1.2   1.3   1.4   2.1   2.2   2.3   2.4

##### University Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

University Graduate Attribute Course Learning Outcome(s)
Deep discipline knowledge
• informed and infused by cutting edge research, scaffolded throughout their program of studies
• acquired from personal interaction with research active educators, from year 1
• accredited or validated against national or international standards (for relevant programs)
1-4
Critical thinking and problem solving
• steeped in research methods and rigor
• based on empirical evidence and the scientific approach to knowledge development
• demonstrated through appropriate and relevant assessment
1-4
Teamwork and communication skills
• developed from, with, and via the SGDE
• honed through assessment and practice throughout the program of studies
• encouraged and valued in all aspects of learning
1-4
Career and leadership readiness
• technology savvy
• professional and, where relevant, fully accredited
• forward thinking and well informed
• tested and validated by work based experiences
1-4
• Learning Resources
##### Required Resources
There are no required resources; lecture notes will be available on the MyUni website.
##### Recommended Resources
• A New Approach to Linear Filtering and Prediction Problems/ R. E. Kalman.
• Stochastic Models, Estimation, and Control/ P. S. Maybeck.
• An Introduction to the Kalman Filter/ G. Welch and G. Bishop
• Kalman Filtering with Its Real-Time Applications/ C. K. Chui and G. Chen
• Kalman Filtering: Theory and Application / edited by H.W. Sorenson.
• Kalman Filtering Techniques for Radar Tracking / K.V. Ramachandra.
• Optimal Filtering / B.D. O. Anderson, J.B. Moore.
##### Online Learning
Extensive use will be made of the MyUni web site for this course, https://myuni.adelaide.edu.au/webapps/login

Course notes, tutorial problems, project requirements, course schedule, group list and a practice exam will all be available for downloading from the website.

Tutorial solutions will NOT be available online

Where the lecture theatre facilities permit, audio or video recordings of lectures will also be available for downloading.
• Learning & Teaching Activities
##### Learning & Teaching Modes

No information currently available.

##### Workload

No information currently available.

##### Learning Activities Summary

No information currently available.

• Assessment

The University's policy on Assessment for Coursework Programs is based on the following four principles:

1. Assessment must encourage and reinforce learning.
2. Assessment must enable robust and fair judgements about student performance.
3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
4. Assessment must maintain academic standards.

##### Assessment Summary
Due to the current COVID-19 situation modified arrangements have been made to assessments to facilitate remote learning and teaching. Assessment details provided here reflect recent updates.  Assessment Task Weighting (%) Individual/ Group Formative/ Summative Due (week)* Hurdle criteria Learning outcomes Assignment 1 25 Individual Formative Week 5 1. 2. 3. Assignment 2 25 Individual Formative Week 10 1. 2. 3. Exam 50 Individual Summative Week 14 Min 40% 1. 2. 3. 4. Total 100
* The specific due date for each assessment task will be available on MyUni.

This assessment breakdown is registered as an exemption to the University's Assessment for Coursework Programs Policy. The exemption is related to the Procedures clause(s):

This course has a hurdle requirement. Meeting the specified hurdle criteria is a requirement for passing the course.

Note that the examination will be conducted without supervision. That is, you will be given the examination paper (electronic version) via MyUni at a given time, and you then return your answers paper by a given time.

##### Assessment Related Requirements
For this course, the minimum exam mark requirement is 40%.
##### Assessment Detail
Each assignment will be counted 15% of the total score of this course.

The final exam will be counted 70% of the total score of this course.
##### Submission

No information currently available.

##### Course Grading

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
Grade Mark Description
FNS   Fail No Submission
F 1-49 Fail
P 50-64 Pass
C 65-74 Credit
D 75-84 Distinction
HD 85-100 High Distinction
CN   Continuing
NFE   No Formal Examination
RP   Result Pending

Further details of the grades/results can be obtained from Examinations.

Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

Final results for this course will be made available through Access Adelaide.

• Student Feedback

The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

• Student Support
• Policies & Guidelines
• Fraud Awareness

Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's studentâ€™s disciplinary procedures.

The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

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