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Proceedings Paper

Information elasticity in pseudorandom code pulse compression
Author(s): Andrew Z. Liu; Ram M. Narayanan; Muralidhar Rangaswamy
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Paper Abstract

Information elasticity is a new concept which characterizes the role of information in making effective decisions in sensor processing. Information elasticity is defined as the ratio of the fractional increase in decision effectiveness to the fractional increase in information. Increasing the quantity of information used in radar processing has the ability to decrease the performance of the radar in certain contexts, depending on what constraints and objectives exist. Because of this phenomenon (known as information overload), it is advantageous to find the optimal amount of information tailored to the specific context the radar is used in. This paper analyzes the process of finding the point of information overload using the information elasticity model. This model is used in observation of different contexts in pseudorandom code pulse compression. In this model, the length of the pseudorandom code represents the amount of information. Increasing this quantity affects both the quality of pulse compression and constraints of the system. We observe this relationship between the constraints and information quantity by developing constraint functions. In this paper, two decision metrics are created for pseudorandom pulse compression, the first based on the peak to side-lobe ratio and the second based on the detection region of the radar.

Paper Details

Date Published: 4 May 2018
PDF: 9 pages
Proc. SPIE 10633, Radar Sensor Technology XXII, 106330F (4 May 2018); doi: 10.1117/12.2305853
Show Author Affiliations
Andrew Z. Liu, The Pennsylvania State Univ. (United States)
Ram M. Narayanan, The Pennsylvania State Univ. (United States)
Muralidhar Rangaswamy, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 10633:
Radar Sensor Technology XXII
Kenneth I. Ranney; Armin Doerry, Editor(s)

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