FIELD: data processing.
SUBSTANCE: invention relates to secondary digital processing of radar signals and can be used for tracking and identification of type of air target (AT) of aircraft with turbojet (TJE) when exposed to signal-like with Doppler frequency modulation, noise of DRFM type (digital radio-frequency memory). Method consists in the fact that reflected from aircraft AT with TJE radar signal by means of fast Fourier transformation procedure is converted into amplitude-frequency spectrum, which components are caused by reflections of signal from airframe escorted AT and low-pressure compressor (LPC) rotating parts of its power plant, as well as exposure to a signal-like DFRM type interference with Doppler frequency modulation. In area of glider components of Doppler frequencies, first, determining a first Doppler frequency count corresponding to a maximum amplitude of the spectral component of the signal spectrum which is transmitted to the input of the first Kalman filter, secondly, determining a second Doppler frequency count corresponding to an amplitude commensurate with the spectral component of the signal spectrum having a maximum amplitude in the region of glider Doppler frequencies, which is transmitted to the input of the second Kalman filter, third, determining a Doppler frequency count corresponding to a maximum amplitude of the spectrum component of the signal spectrum lying on the left per kHz units from the Doppler frequency relative to the first and second Doppler frequency samples, which is supplied to input of Kalman filter of the first compressor component of signal spectrum, which is caused by reflections of signal from impeller blades of first stage LPC. At each cycle of operation of three Kalman filters, estimating, respectively, the difference between the estimated first Doppler frequency values and the first target airship LPC first stage LPC blades with TJE blades and between the estimated second Doppler frequency values and the first stage LPC impeller blades. Difference difference moduli derivatives are determined, which are compared with a threshold value ε close to zero. Entire range of possible values of estimates of differences is a priori broken down into Q non-overlapping subranges. For K of intermediate cycles of operation of all three Kalman filters, probability Pq of falling of formed value into each of a priori formed q-th sub-range is determined. Number of the q-th sub-range for which the probability Pq is maximum is determined. This is the maximum value of Pq max is compared with predetermined threshold probability of target type recognition Pthr. If Pq max≥Pthr, decision is made on recognition of the q-type of the accompanied AT-aircraft with TJE with probability Pq max, not lower than the specified one, otherwise, decision is made on impossibility to recognize type of escorted AT with specified probability.
EFFECT: with probability of at least a given type of accompanied AT-aircraft with TJE under action of signal-like with Doppler frequency modulation of DRFM type interference.
1 cl, 2 dwg
Title | Year | Author | Number |
---|---|---|---|
METHOD OF TRACKING AERIAL TARGET FROM "TURBOJET AIRCRAFT" CLASS UNDER EFFECT OF VELOCITY DEFLECTING NOISE | 2015 |
|
RU2579353C1 |
METHOD OF AIRCRAFT TYPE IDENTIFICATION WITH TURBOJET ENGINE IN PULSE-DOPPLER RADAR STATION UNDER ACTION OF SIMULATING NOISE | 2020 |
|
RU2735314C1 |
A METHOD FOR RECOGNIZING THE TYPICAL COMPOSITION OF A GROUP AIR TARGET FROM THE CLASS "TURBOJET ENGINE AIRCRAFTS" BASED ON KALMAN FILTERING AND A NEURAL NETWORK | 2022 |
|
RU2786518C1 |
METHOD OF TRACKING CLUSTERED AIR TARGET FROM 'TURBOJET AIRCRAFT' CLASS | 2011 |
|
RU2456633C1 |
METHOD OF TRACKING AIR TARGET OF "TURBOJET ENGINE AIRCRAFT" CLASS | 2009 |
|
RU2419815C1 |
METHOD OF AIRCRAFT WITH TURBOJET ENGINE TYPE IDENTIFICATION IN PULSE-DOPPLER RADAR STATION UNDER ACTION OF SPEED-ESCAPING INTERFERENCE | 2019 |
|
RU2732281C1 |
METHOD TO SUPPORT GROUP AIR TARGETS OF "AIRCRAFT WITH TURBOJET" CLASS IN RADAR LOCATION STATION AT EXPOSURE OF RATE INTERFERENCE | 2016 |
|
RU2617110C1 |
METHOD FOR RECOGNIZING TYPICAL COMPOSITION OF A CLUSTERED AIR TARGET OF VARIOUS CLASSES UNDER VARIOUS CONDITIONS OF THEIR FLIGHT BASED ON KALMAN FILTERING AND A NEURAL NETWORK | 2022 |
|
RU2802653C1 |
METHOD OF TRACKING AERIAL TARGET FROM “TURBOJET AIRCRAFT” CLASS UNDER EFFECT OF RANGE AND VELOCITY DEFLECTING NOISE | 2018 |
|
RU2665031C1 |
METHOD FOR ALL-ANGLE RECOGNITION IN RADAR STATION OF TYPICAL COMPOSITION OF GROUP AIR TARGET UNDER VARIOUS FLIGHT CONDITIONS AND INFLUENCE OF SPEED-CONTUSION INTERFERENCE BASED ON KALMAN FILTERING AND NEURAL NETWORK | 2023 |
|
RU2816189C1 |
Authors
Dates
2020-07-28—Published
2020-01-21—Filed