Minimization of Error Source
The performance of practical geo-location systems can be improved in several ways.
DF Techniques. The performance of DF systems can vary widely, depending on the implementation and choice of deployment sites:
1. System design choices and trade-offs need to be considered carefully. Antenna arrays with large baselines tend to have performance advantages, but they are generally undesirable for tactical applications. Conversely, attempts to cover a large frequency range with a single antenna array involve significant challenges;
2. Gain and phase mismatches contributed by the receiver hardware and the cables between the antenna and receiver can be corrected by measuring the errors and subtracting them from future measurements. The errors can be measured by using a suitable signal source and radio frequency switch to apply a calibration signal at the point where the cables connect to the antenna. Measurements obtained at suitably chosen test frequencies can be used to construct a calibration table containing the amplitude and phase-correction factors required at each of the test frequencies;
Systematic errors contributed by the antenna can be corrected using a calibration table to provide correction values to be subtracted from the measurements. A one-dimensional calibration table can be constructed by carrying out controlled tests using signals transmitted from a fixed angle at frequencies spaced through the frequency range covered by the system and measuring the discrepancy between the actual and observed angles.
Because the errors generally must be angle dependent, the use of a two-dimensional calibration table is desirable. This table can be constructed by the repeating the procedure for angles distributed around the full 360° interval. Interpolation can be used to generate calibration values for intermediate frequencies and angles.
3. The choice of sites for the deployment of DF systems is critical. Ideally, the site should be free of features that contribute to multipath propagation, and line-of- sight propagation should be possible over the area of interest. In these respects, the elevation of the antenna is an important factor. Another consideration is that the sites should be selected to provide favorable sensor-target geometries for geo-location via triangulation.
4. Geo-location performance improves as the number of sites from which DF information is available increases.
TDOA and FDOA Techniques. The performance of TDOA and FDOA geo-location systems is sensitive to system-implementation choices, the nature of the signals of interest, and various aspects of the system deployment:
1. If the system operation is dependent on the relaying of signals received at the sensor sites to a common site for processing, the system must be able to perform this function without significantly degrading the quality of the signals.
2. Provisions must be made to account for the delays contributed by the relaying of the signals observed at the sensor sites to a common site; these delays must be removed or accounted for.
3. The performance of TDOA estimation processing depends on the signal-to-noise ratio and the presence of suitable information contained in the signal modulation. Narrowband signals may require higher signal-to-noise ratios and/or longer observation times to achieve the desired accuracy;
Frequency shifts that result from relative motions of the receivers and transmitter affect TDOA measurement processing. If, for scenarios of interest, they are sufficiently important, then provisions must be made in the TDOA estimation processing to remove them. If FDOA information is used for geo-location, then the most favorable results will be obtained when the sensors move rapidly, because this action increases the relative frequency shifts, and a given error in frequency measurement becomes less significant. Also, uncertainties contributed by the movement of the signal source are reduced.
Bibliography:
1. D. C. Schleher, Electronic Warfare in the Information Age, Norwood, MA: Artech House, 1999.
2. R. Poisel, Introduction to Communications Electronic Warfare Systems, Norwood, MA: Artech House, 2002.
3. A. Price, Instruments of Darkness: The History of Electronic Warfare, Encore Editions, 1978.
4. A. Price, The History of US Electronic Warfare, Volume 1, The Years of Innovation-Beginnings to 1946, Norwood, MA: Artech House, 1984.
5. R. V. Jones, Most Secret War, London, UK: Hamish Hamilton, 1978.
6. M. Arcangelis, Electronic Warfare: From the Battle of Tsushima to the Falklands and Lebanon Conflicts, Dorset, United Kingdom: Blandford Press, 1985.
7. A. Price, The History of US Electronic Warfare, Volume II, The Renaissance Years, 1946 to 1964, Norwood, MA: Artech House, 1989.
8. A. Price, The History of US Electronic Warfare, Volume III, Rolling Thunder Through Allied Force, 1964to2000, Norwood, MA: Artech House, 2000.
9. P. Mihelich, Jamming systems play secret role in iraq, Available: http://www.cnn.com/2007/TECH/08/13/cied.jamming.- tech/index.html.
10. R. J. Hanyok, Spartans in Darkness: American SIGINT and the Indochina War, 1945-1975, Vol. 7, Center for Cryptologic History, National Security Agency, 2002.
11. D. Eshel, EW in the Yom Kippur War, J. Electronic Defense, 30(10): 2007.
12. Joint Publication 3-13.1,Electronic Warfare, January 25,2007, Available: http://www.fas.org/irp/doddir/dod/jp3-13-1.pdf.
13. M. Streetly (ed.), Janes Radar and Electronic Warfare Systems 2005-2006, Surrey, UK: Jane’s Information Group, 2005.
14. P. W. East, ESM Range Advantage, IEE Proc., 144(4): 1985.
15. R. G. Wiley, ELINT: The Interception and Analysis of Radar Signals, Norwood, MA: Artech House, 2006.
16. R. A. McDonald and S. K. Moreno, Raising the periscope ... grab and poppy: america’s early ELINT satellites, Center for the Study of National Reconnaissance, National Reconnaissance Office, Chantilly, VA, September 2005.
17. P. Hill, E. Adams, andV. Comley, Techniques for detecting and characterizing covert communications signals, Proc. European Conference on Security and Detection, April 1997.
18. R. Inkol, S. Wang, and S. Rajan, FFT filter bank-based CFAR detection schemes, Proc. of Midwest Symposium on Circuits and Systems, August 5-8, 2007.
19. Y. T. Chan and L. G. Gadbois, Identification of the modulation type of a signal, Signal Processing, 16(2): 1989.
20. K. Nandi and E. E. Azzouz, Algorithms for automatic modulation recognition of communication signals, IEEE Trans. Commun., 40(4): 1998.
Date added: 2024-02-23; views: 172;