Non-linear dynamics method for target identification
Non-linear dynamics method for target identification
- Author(s): T.L. Carroll and F.J. Rachford
- DOI: 10.1049/iet-rsn.2010.0381
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- Author(s): T.L. Carroll 1 and F.J. Rachford 1
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View affiliations
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Affiliations:
1: US Naval Research Lab, Washington, USA
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Affiliations:
1: US Naval Research Lab, Washington, USA
- Source:
Volume 5, Issue 7,
August 2011,
p.
741 – 746
DOI: 10.1049/iet-rsn.2010.0381 , Print ISSN 1751-8784, Online ISSN 1751-8792
One may describe the effect of a radar or sonar target on an incoming signal as a filter that produces a scattered signal. Chaotic signals are very sensitive to the effect of filters, and so a radar or sonar target imposes a unique signature on a scattered chaotic signal. In this study the authors describe a method that uses the concept of phase space dimension to create a reference from a scattered chaotic signal. This reference becomes part of a library, and comparing an unknown scattered signal to this library can reveal which target caused a particular scattered signal. As the authors are not imaging the target, this method can use signal with low-range resolution.
Inspec keywords: radar signal processing; filtering theory; sonar
Other keywords:
Subjects: Sonar and acoustic radar; Filtering methods in signal processing
References
-
-
1)
- E. Kennaugh . The K-pulse concept. IEEE Trans. Antennas Propag. , 2 , 327 - 331
-
2)
- A. Taflove . (2000) Computational electrodynamics: the finite difference time domain method.
-
3)
- L.M. Pecora , L. Moniz , J. Nichols , T.L. Carroll . A unified approach to attractor reconstruction. Chaos, Interdiscip. J. Nonlinear Sci. , 1 , 013110 - 013119
-
4)
- B. Flores , E.A. Solis , G. Thomas . Assessment of chaos-based FM signals for range-Doppler imaging. IEEE Proc. Radar Sonar Navig. , 4 , 313 - 322
-
5)
- J. Bednar . On the approximation of FIR by IIR digital filters. IEEE Trans. Acoust. Speech Signal Process. , 1 , 28 - 34
-
6)
- R. Badii , G. Broggi , B. derighetti , M. Ravini , S. Ciliberto , A. Politi . Dimension increase in filtered chaotic signals. Phys. Rev. Lett. , 11
-
7)
- H. Kantz , E. Olbrich . Scalar observations from a class of high-dimensional chaotic systems: limitations of the time delay embedding. Chaos , 3 , 423 - 429
-
8)
- D.S. Broomhead , J.P. Huke , M.R. Muldoon . Linear filters and non-linear systems. J. R. Stat. Soc. B (Methodological) , 2 , 373 - 382
-
9)
- Willett, P., Reinert, J., Lynch, R.: `LPI waveforms for active sonar?', Proc. IEEE Aerospace Conf. (IEEE Cat. No. 04TH8720), 2004, 2234, p. 2236–2248.
-
10)
- M.B. Kennel , R. Brown , H.D.I.A. Abarbanel . Determing embedding dimension for phase-space reconstruction using a geometrical construction. Phys. Rev. A , 3403 - 3411
-
11)
- K.A. Lukin . Noise radar technology. Telecommun. Radio Eng. , 12 , 8 - 16
-
12)
- Bergin, J.S., Techau, P.M., Carlos, J.E.D., Guerci, J.R.: `Radar waveform optimization for colored noise mitigation', Proc. IEEE Radar Conf., 2000, Alexandria, VA, p. 149–154.
-
13)
- T.S. Parker , L.O. Chua . (1989) Practical numerical algorithms for chaotic systems.
-
14)
- P.R. Atkins , A.J. Fenwick . Chaotic signals in a multipath channel. Proc. Inst. Acoust. , 5 , 154 - 162
-
15)
- M. Vespe , C.J. Baker , H.D. Griffiths . Automatic target recognition using multi-diversity radar. Radar Sonar Navig., IET , 6 , 470 - 478
-
16)
- H.D.I. Abarbanel , R. Brown , J.J. Sidorowich , L.S. Tsmring . The analysis of observed chaotic data in physical systems. Rev. Mod. Phys. , 4 , 1331 - 1392
-
17)
- Quach, B., Leung, H., Lo, T., Litva, J.: `Radar target identification using multifractal geometry', Proc. SPIE, 1996, 2755, p. 594–605.
-
18)
- J.D. Farmer , E. Ott , J.A. Yorke . The dimension of chaotic attractors. Phys. D, Nonlinear Phenom. , 153 - 180
-
19)
- S.U. Pillai , H.S. Oh , D.C. Youla , J.R. Guerci . Optimum transmitðreceiver design in the presence of signal-dependent interference and channel noise. IEEE Trans. Inf. Theory , 2 , 577 - 584
-
20)
- L. Fortuna , M. Frasca , A. Rizzo . Chaotic pulse position modulation to improve the efficiency of sonar sensors. IEEE Trans. Instrum. Meas. , 6 , 1809 - 1814
-
21)
- J.-P. Eckmann , S.O. Kamphorst , D. Ruelle , S. Ciliberto . Liapunov exponents from time series. Phys. Rev. A , 4971 - 4979
-
22)
- B.R. Mahafza . (2000) Radar systems analysis and design using MATLAB.
-
23)
- F.Y. Lin , J.M. Liu . Chaotic radar using nonlinear laser dynamics. IEEE J. Quantum Electron. , 6 , 815 - 820
-
24)
- Hara, Y., Hara, T., Seo, T., Yanagisawa, H., Ratliff, P., Machowski, W.: `Development of a chaotic signal radar system for vehicular collision-avoidance', Proc. IEEE Radar Conf. (IEEE Cat. No. 02CH37322), 2002, p. 227–232.
-
25)
- T.L. Carroll . Optimizing chaos-based signals for complex radar targets. Chaos , 3
-
26)
- V. Venkatasubramanian , H. Leung . A novel chaos-based high-resolution imaging technique and its application to through-the-wall imaging. IEEE Signal Process. Lett. , 7 , 528 - 531
-
27)
- A.W. Rihaczek , S.J. Hershkowitz . (2000) Theory and practice of radar target identification.
-
1)
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