CORRELATION METHOD FOR FORMING THE TRAINING SAMPLE FOR ADAPTATION OF THE SPATIAL FILTER

Authors

  • D. M. Piza Zaporozhye National Technical University, Zaporozhye, Ukraine., Ukraine
  • S. N. Romanenko Zaporozhye National Technical University, Zaporozhye, Ukraine., Ukraine
  • D. S. Semenov State Enterprise “Scientific and Production Complex “Iskra”, Zaporozhye, Ukraine, Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2018-3-4

Keywords:

adaptive spatial processing, combined interference, classified training sample, modeling.

Abstract

Contex. To ensure noise immunity of modern radar stations, two-stage space-time signal processing is used. However, with
simultaneous exposure to active and passive interference, the latter decorrelates the active interference. This significantly limits the
noise immunity of coherent-impulse radar stations. Therefore, the formation of a classified training sample, generated only by active
noise interference, is quite important task.
Objective. The aim of the work is to investigate the correlation method for the formation of a classified learning sample in real
time by the current analysis of the interchannel correlation coefficient module over distance in each period of repeating the radar
signal.
The method is realized by forming an interval synchronous evaluation of both the interchannel correlation coefficient modulus
and the spatial filter weight coefficients. In this case, the interval with the maximum value of the interchannel correlation coefficient
modulus is defined as the classified training sample, and the weight coefficient formed on this interval is used to adapt the spatial
filter weight factor when the active noise interference is compensated in the next period of repeating the signals of the radar.
Results. The theoretical and practical aspects of the formation of the classified training sample are considered. It was developed a
block diagram of the spatial filter with a correlation analysis of the current passive interference distribution over distance by estimating
the interchannel correlation coefficient modulus of the signals acting in the channels of the spatial filter. A mathematical model
of the adaptive spatial filter was developed and tested. The possibility of working a spatial filter with the formation of a classified
training sample in real time has been confirmed.
Conclusions. The scientific novelty of the study is to further develop a new method for the formation of a classified training sample for the adaptation of a spatial filter. It is shown that the current analysis of the module of the interchannel correlation coefficient allows in real time to determine the interval on which there is no passive interference and to form a training sample for adaptation of the weight coefficients of the spatial filter.

References

Zhuravlev A. K., Hlebnikov V. A., Rodimov A.P. i dr.

Adaptivnye radiotehnicheskie sistemy s antennymi reshotkami. Leningrad, Izd. Leningradskogo universiteta,1991, 544 p.

Abramovich JU. I., Kachur V. G. Bystrodeistvie poocherednoj

nastroiki razdel’nyh sistem zashity ot kombinirovannyh

pomeh, Radiotehnika i elektronika, 1969, Vyp. 1, pp. 52–58.

Abramovich JU. I. Predel’naja skorost’ shodimosti

processov adaptivnoj nastrojki sistem kompensacii pomeh v

uslovijah neklassificirovannoj obuchajushej vyborki,

Radiotehnika i elektronika, 1982, Vyp. 8, pp. 1534–1538.

Grigor’ev V. V. Kombinirovannaja obrabotka signalov v

sistemah radiosvjazi. Moscow, EKO-TRENDZ, 2002, 262 p.

Piza D. M., Zvjagincev E. A., Moroz G. V. Metod

kompensacii aktivnoj sostavljajushej kombinirovannoj

pomehi v kogerentno-impul’snoj RLS, Izvestija vysshih

uchebnyh zavedenij. Radioelektronika, 2016, No. 6, pp. 23–

DOI: 10.20535/S0021347016060030.

Piza D. M., Moroz G. V. Metody formirovanija

klassificirovannoj obuchajushej vyborki dlja adaptacii

vesovyh koefficientov avtokompensatora pomeh, Izvestija

vysshih uchebnyh zavedenij. Radioelektronika, 2018, No. 1,

pp. 47–54.

Monzingo R. A., Miller T. U. : per. s angl. pod red. Leksachenko V. A. Adaptivnye antennye reshotki: vvedenie v teoriju. Moscow, Radio i svjaz’, 1986, 445 p.

Ivlev D. N., Orlov I. JA., Sorokina A. V., Fitasov E. S.

Adaptivnye algoritmy kompensacii pomeh: uchebnometodicheskoe posobie ; Min-vo obrazovanija I nauki RF, Nizhnenovgorodskij gos. universitet im. N. I. Lobachevskogo. Nizhnij Novgorod, NNGU im. N. I. Lobachevskogo, 2014, 8 p.

Piza D. M., Lavrent’ev V. N., Semenov D. S. Metody formirovanija klassificirovannoj obuchajushej vyborki dlja avtokompensatora pomeh pri vremja-prostranstvennoj fil’tracii

signalov, Radio Electronics, Computer Science, Control, 2016,

No. 3, pp. 18–22. DOI: 10.15588/1607-3274-2016-3-2.

Bespalov D. P. i dr.; red. : Surygina L.K Atlas oblakov /

Fever. Sluzhba po gidrometeorologii i monitiringu okruzhajushej sredy (Ros-gidromet), Gl. geofiz. observatorija im. A. I. Voejkova. Sankt-Peterburg, D’ART, 2011, 248 p.

Shirman JA. D. Razreshenie i szhatie signalov. Moscow,

Sov. radio, 1974, 360 p.

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How to Cite

Piza, D. M., Romanenko, S. N., & Semenov, D. S. (2018). CORRELATION METHOD FOR FORMING THE TRAINING SAMPLE FOR ADAPTATION OF THE SPATIAL FILTER. Radio Electronics, Computer Science, Control, (3). https://doi.org/10.15588/1607-3274-2018-3-4

Issue

No. 3 (2018): Radio Electronics, Computer Science, Control

Section

Radio electronics and telecommunications

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Copyright (c) 2018 D. M. Piza, S. N. Romanenko, D. S. Semenov

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