Narresh Vankayalapati (University of Rhode Island), “Direct position detection and localization of emitters using distributed sensors” (2012)

You are here

Inside Signal Processing Newsletter Home Page

Top Reasons to Join SPS Today!

1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.

News and Resources for Members of the IEEE Signal Processing Society

Narresh Vankayalapati (University of Rhode Island), “Direct position detection and localization of emitters using distributed sensors” (2012)

Narresh Vankayalapati (University of Rhode Island), “Direct position detection and localization of emitters using distributed sensors”, Advisor: Prof. Steven Kay, (2012)

In this thesis, the author addressed the problem of passively gathering information about an emitter of electronic signals using distributed sensors. First, the author proposed an asymptotically optimal technique for detection of the presence or absence of such signals in the data collected at the distributed sensors. This is a centralized detector unlike the commonly used decentralized decision fusion techniques. After the presence of such signals is detected, the next step is to estimate the location of the emitter. Since the conventional time difference of arrivals TDOA technique has been approved to be sub-optional compared with the direct position determination (DPD) approach, the author took the DPD approach and proposed a MLE. The DPD type localizers that have been proposed in the literature are based on certain assumptions on the transmitted signal such as narrowband or wideband, lowpass or bandpass etc. The proposed approach makes no such assumptions on the signal and this paper covers a wide variety of transmitted signals. It is shown that that the proposed MLE outperforms the conventional two-step localizers and also attains the Cramer Rao Lower Bound (CRLB) for high signal-to-noise ratios (SNR).

For details, please read the full version of the thesis or contact the author.

Table of Contents:

SPS Social Media

IEEE SPS Educational Resources

IEEE SPS Resource Center

IEEE SPS YouTube Channel