Optimization method for a radar situation interface from error-cognition to information feature mapping

doi:10.23919/JSEE.2022.000090

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (4): 924-937.doi: 10.23919/JSEE.2022.000090

• DEFENCE ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

Optimization method for a radar situation interface from error-cognition to information feature mapping

Xiaoli WU^1,^2,³(), Wentao WEI^1,*(), Sabrina CALDWELL⁴(), Chengqi XUE²(), Linlin WANG²()

¹ School of Design Art & Media, Nanjing University of Science & Technology, Nanjing 210094, China
² School of Mechanical Engineering, Southeast University, Nanjing 211189, China
³ College of Mechanical and Electrical Engineering, Hohai University, Changzhou 211100, China
⁴ School of Computer Science, Australian National University, Canberra 2600, Australia

Received:2021-01-11 Accepted:2022-06-28 Online:2022-08-30 Published:2022-08-30
Contact: Wentao WEI E-mail:wuxlhhu@163.com;weiwentao@njust.edu.cn;sabrina.caldwell@anu.edu.au;ipd_xcq@seu.edu;353248644@qq.com
About author:|WU Xiaoli was born in 1980. She received her Ph.D. degree in 2015 from the College of Mechanical Engineering, Southeast University. She is currently a professor and doctoral supervisor in the School of Design Art & Media, Nanjing University of Science & Technology (NJUST). She had a one-year experience of research scholar in the the Research School of Computer Science, Australian National University. She mainly engages in human-computer interaction and visualization design research. E-mail: wuxlhhu@163.com||WEI Wentao was born in 1989. He received his Ph.D. degree from the College of Computer Science and Technology, Zhejiang University, Hangzhou, China, in 2018. He is currently a lecturer with the School of Design Art & Media, Nanjing University of Science and Technology, Nanjing, China. His current research interests include natural user interaction, biomedical signal processing and deep learning. E-mail: weiwentao@njust.edu.cn||CALDWELL Sabrina received her Ph.D. degree from the College of Arts and Social Sciences and College of Engineering and Computer Science, Australian National University. She is currently a researcher at Australian National University. She received her second Ph.D. degree in 2017, undertaken in the School of Computer Science. Her area of research is photography, specifically photo credibility. E-mail: sabrina.caldwell@anu.edu.au||XUE Chengqi was born in 1961. He received his Ph.D. degree from the College of Mechanical Engineering, Southeast University in 1988. He is a professor and a doctoral supervisor working in the School of Mechanical Engineering, Southeast University, China. His research intrests include industrial product design and usability engineering and man-machine interface design. E-mail: ipd_xcq@seu.edu||WANG Linlin was born in 1995. She received her M.S. degree in 2018 from the School of Mechanical and Electrical Engineering, Hohai University. She is currently a Ph.D. candidate in the School of Mechanical Engineering, Southeast University. She is engaged in the research on visualization method and evaluation mechanism of intelligent interactive interface with human-computer fusion. E-mail: 353248644@qq.com
Supported by:
This work was supported by Jiangsu Province Nature Science Foundation of China (BK20221490), the Key Fundamental Research Funds for the Central Universities (30920041114), the National Natural Science Foundation of China (52175469;71601068), the Key Research and Development (Social Development) Project of Jiangsu Province (BE2019647), and Jiangsu Province Social Science Foundation of China (20YSB013).

Abstract

Abstract:

With the rapid development of digital and intelligent information systems, display of radar situation interface has become an important challenge in the field of human-computer interaction. We propose a method for the optimization of radar situation interface from error-cognition through the mapping of information characteristics. A mapping method of matrix description is adopted to analyze the association properties between error-cognition sets and design information sets. Based on the mapping relationship between the domain of error-cognition and the domain of design information, a cross-correlational analysis is carried out between error-cognition and design information. We obtain the relationship matrix between the error-cognition of correlation between design information and the degree of importance among design information. Taking the task interface of a warfare navigation display as an example, error factors and the features of design information are extracted. Based on the results, we also propose an optimization design scheme for the radar situation interface.

Key words: radar situation interface, error-cognition, information feature mapping, visual information display

Xiaoli WU, Wentao WEI, Sabrina CALDWELL, Chengqi XUE, Linlin WANG. Optimization method for a radar situation interface from error-cognition to information feature mapping[J]. Journal of Systems Engineering and Electronics, 2022, 33(4): 924-937.

Figures/Tables 10

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References 36

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Interface	Task
Task of monitoring interface A	A1 monitor/discover	A2 inquire state	A3 plan response	A4 execute response
Display format of information B	B1 dynamic display	B2 static display	B3 navigation	B4 status data
Display format of information B	B5 information icon	B6 alarm reminder
Cognitive behavior C	C1 search	C2 recognize	C3 identify	C4 judge＆select
Cognitive behavior C	C5 make decisions
Error factor D	D1 ignorance	D2 omission	D3 miss	D4 misreading
	D5 misjudgment	D6 misunderstanding	D7 haven’t seen	D8 confusion
	D9 cannot remember	D10 input error	D11 misregistration	D12 cannot see clearly
	D13 hard to distinguish	D14 match incorrectly	D15 cannot find	D16 delay
	D17 inadequate	D18 irrelevant	D19 react too early	D20 no reaction
	D21 select incorrectly	D22 slip
Representation of error E	E1 ambiguity states	E2 visual limitation	E3 visual bluntness	E4 visual illusion
	E5 attentional load	E6 visual disturbance	E7 overattention	E8 attention shift and distraction
	E9 too nervous to do anything	E10 cognitive bias	E11 unreasonable match	E12 weak visibility
	E13 thinking load	E14 forget	E15 inaccurate recall	E16 lack of memory aids
	E17 intentionality	E18 false memory	E19 unconsciousness	E20 omission caused by inattention
	E21 time pressure

Information feature	Monitoring/discovery	Status inquiry	Response planning	Response execution
c_q1	0.55	0.25	0.125	0.175
c_q2	0.35	0.45	0.08	0.12
c_q3	0.25	0.55	0.175	0.025
c_q4	0.35	0.35	0.125	0.175
c_q5	0.25	0.25	0.375	0.175
c_q6	0.125	0.225	0.35	0.3
c_q7	0.375	0.325	0.155	0.145

Information feature	Monitoring/discovery	Status inquiry	Response planning	Response execution
p_i	0.55	0.25	0.125	0.175
1/p_i	1.82	4.00	8.00	5.71
log₂ (1/p_i)	0.86	2.00	3.00	2.51

Objective constraint	RMC	Information capacity	Visual flow	Graphic-element relation	Task level	Relative weight
RMC	1	3	2	1/2	1/3	0.170
Information capacity	1/3	1	1/2	1/3	1/5	0.068
Visual flow	1/2	2	1	1/2	1/3	0.118
Graphic-element relation	2	3	2	1	1/2	0.237
Task level	3	5	3	2	1	0.407

Optimization method for a radar situation interface from error-cognition to information feature mapping

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