RU2407031C1 - Radar device for classifying vibrating aircraft with flight path instabilities in surface layers - Google Patents

Abstract

FIELD: physics. ^ SUBSTANCE: disclosed device has a synchroniser, a modulator, a microwave oscillator, an antenna switch, a receiver, a range measuring system, a resolver, an antenna, an antenna control system, a velocity measuring system, three analogue-to-digital converters, memory, a fast Fourier transformation computer, a classification unit, designed and connected to each other in a certain way. ^ EFFECT: high quality of classifying location objects according to the structure of a vibration map owing to further consideration of phase information of reflected signals, owing to exclusion of components arising from direct reflection from the body of an object and presence of scanning frequencies, and owing to averaging of negative spectral components of the turbo-prop effect. ^ 1 dwg

Description

The invention relates to the field of radar measurements and can be used in pulsed radars with conical scanning to classify various air objects.

Known radar method for the study of vibrating objects and a device for its implementation [1], based on the selection of periodic components in the reflected signal when irradiating nearby vibrating objects. The device presented in [1] contains a transceiver antenna, the input-output of which through the circulator is connected to the input of the demodulator, and the output of the modulator is connected to another input of the circulator, an amplifier connected to the output of the modulator, the output of which is connected simultaneously with the first input of the second controlled key, the input of the amplitude detector and the first input of the first managed key, the output of which is connected to the input of the spectrum analyzer, and the second input - simultaneously with the output of the comparator and the input of the delay unit, the output of which is connected chen to the second input of the second controllable switch, the third input of which is grounded, and an output connected to a second modulator input, the first (signal) input coupled simultaneously with output of the generator and the local oscillator input of the demodulator. The output of the amplitude detector is connected to the first input of the comparator, the second input of which is connected with the output of the threshold block.

This device allows with high accuracy to determine the vibrational characteristics of the objects of the bearing from the scattered radar signals. Since various objects, due to the specifics of their shape, have different vibrational characteristics, the proposed device can be considered a device that provides classification of various vibrating objects. However, this device cannot be used to classify objects such as aerodynamic aircraft (LA), vibrating during trajectory flight instabilities in a turbulent atmosphere, since it only functions correctly when locating nearby objects in order to neglect the delay time of the scattered signal, used repeatedly was justified.

In [2], a description is given of another radar device for classifying objects by amplitude-modulated echo signals. The use of the device is based on the fact that the reflecting surfaces of the aircraft during their normal functioning make oscillatory movements due to the operation of the engines. The probe pulses of the radar stations react to these oscillations, and the phase of the scattered signals changes in accordance with the oscillation frequency of the object under study. The device includes an antenna, an antenna switch (AP), a receiver, a transmitter, a circular viewing indicator (PPI) and a classification channel consisting of a delay line (LZ), a second key, a mixer, a low-pass filter (LPF) and a device for reproducing an image of an object, The transmitter consists of a modulator, a microwave generator and a first key. In the described device, the antenna is connected through the AP to the input of the receiver and the output of the first key, the second input of which is connected simultaneously with the output of the microwave generator and the second input of the mixer, the output of which is connected to the input of the low-pass filter, and the first input is connected to the output of the second key, the first input of which is connected simultaneously with the output of the receiver and the second input of the IKO, the first input of which is connected simultaneously with the output of the modulator, the first (control) input of the first key and the input LZ, the output of which is connected to the second (control) input of the second key, and The image reproduction facility of the object is connected to the output of the low-pass filter.

The disadvantage of this device is that it cannot provide a high quality classification (separation into classes) of airborne objects, since the classification is carried out using headphones by the color of the sound, which depends on the amplitude and frequency of the vibrations that occur during the flight. The lack of accurate sound standards and the various auditory and identification capabilities of the classification radar operators are the causes of possible errors. If, as a sign of identification, we apply not the timbre of sound, but the distribution of spectral responses over the frequencies of the vibrational range, then in this case the classification probability will not be high either, since this does not take into account the angle of motion of the center of mass of the object and its speed relative to the locator, from which the structure of the frequency portrait of the vibrational range depends. In addition, the device [2] does not track an object, but only its gating in range, which can lead to signals entering into the working distance scattered by several objects and to an increase in classification errors.

Also known is a radar device for classifying objects [3], which includes sequentially connected synchronizer, modulator, microwave generator, AP, receiver, range measuring system (LED) and computer (SRP), as well as an antenna and antenna control system (SUA), the first analog-to-digital converter (ADC), a storage device (memory), a speed measuring system (SIS), a fast Fourier transform computer (FFT), and a classification unit consisting of a microprocessor, a sample selection unit, and a block output classification results. The synchronizer output is connected to the second input of the LED, the first input of which is connected to the input of the ACS and the input of the first ADC, the output of which is connected to the first input of the storage device, the output of which is connected to the input of the FFT computer, the output of which is connected to the first input of the microprocessor, the output of which is connected with the input of the classification results output unit (BRVK), and the second input with the output of the standard selection unit, the first input of which is connected to the output of the speed measuring system, and the second to the output of the computer, the second the course of which is connected to the second output of the control system, the first output of which is mechanically connected to the antenna, the input-output of which is connected to the input-output of the antenna switch, and the second output of the receiver is connected to the input of the ICS.

This device has a higher likelihood of classifying airborne objects by taking into account additional factors when choosing standards for identifying the vibrational range (standards for vibrational portraits, i.e., standards for low-frequency spectra of reflected signals in the distribution range of components of the vibration effect, occupying a frequency band of ± 500 Hz relative to the main Doppler component). However, this device also has significant disadvantages that reduce its efficiency. Firstly, when forming the spectrum of vibrations (vibration portrait), only the amplitude envelope of the reflected signal is used as the initial information, which leads to portrait symmetry in the region of negative and positive frequencies relative to the main Doppler component of the reflected signal. However, the differences in the amplitudes in the regions of positive and negative frequencies of the components of the vibration portrait (VP) contain important information that contributes to a more efficient classification. Secondly, in the frequency range used, in addition to vibrational components, there are also hull (for aircraft - glider) components, referred to as the Doppler portrait of an object [4], as well as components of the scanning frequencies of the antenna directivity (ANA). These components, as a rule, are higher in amplitude than the components of the vibration effect [5], which, when normalizing the portrait, leads to a decrease in the amplitudes of vibration harmonics to practically the noise level and side lobes of more powerful components. This makes it necessary to remove from the processing the components of the airframe of the aircraft and scanning frequencies. And finally, at recommended radar pulse repetition frequencies of the order of several tens of kilohertz, the high-frequency spectral components of the turboprop effect penetrate the range of the low-frequency spectrum used for classification [6, 7], which must be neutralized (eliminated) so that the information contained in the airspace is not distorted [8 ].

The objective of the invention is to improve the quality of classification of location objects according to the structure of the vibration portrait by additionally taking into account the phase information of the reflected signals, by eliminating the components due to direct reflections from the object’s body and the presence of scanning frequencies, as well as by eliminating the negative false spectral components of the turboprop effect (TVE )

To achieve this goal, it is proposed to supplement the device circuit [3] with four additional units: the second and third ADCs, a smoothing unit, a unit for limiting and normalizing the vibration portrait (BONVP), designed to cut out the data representing the Doppler portrait of the aircraft from the generated vibration portrait, and harmonics caused by the presence of a conical scan of the directivity of the antenna. At the same time, it is proposed that BONVP be included in the classification block and associate its output with the first input of the microprocessor, designed to identify the standards with the working vibrational portrait of the aircraft and decide on its class for the greatest degree of similarity. It is proposed to connect the BONVP input to the output of the FFT calculator. It is proposed to connect the input of the FFT calculator to the output of the smoothing unit, the input of which should be connected to the output of the memory, the second input of which is proposed to be connected to the output of the second ADC, the input of which should be connected to the second output of the receiver. The input of the third ADC is proposed to be connected to the SIS output, and the output to the third input of the memory. New circuit elements are known and are digital devices on microprocessors and memory registers, analogues of which are already used in the prototype [3].

The proposed construction of a scheme for a radar classification device for vibrating aircraft makes it possible to significantly improve the quality of determining their classes by additionally taking into account the phase information of the reflected signals, by eliminating the components caused by direct reflections from the object’s body (glider components) and the presence of scanning frequencies, by eliminating negative spectral components TVE, due to obtaining an asymmetric VP of the object in digital form and a more thorough comparison of it with n boron standards are similar in structure.

The drawing shows a structural diagram of a radar device for classifying vibrating aircraft with trajectory flight instabilities in the surface layers of the atmosphere. The radar classification device contains a microwave generator 1, modulator 2, synchronizer 3, antenna 4, AP 5, receiver 6, LED 7, SUA 8, 1st ADC 9, memory 10, SRP 11 (which is designed to calculate the spatial view of the location of the aircraft ), SIS 12, FFT calculator 13, smoothing block 18, 2nd ADC 19, third ADC 20, as well as classification block 17, consisting of a block for outputting classification results 14, a block for selecting standards 15, a microprocessor 16, and BOPVP 21. In contrast from the prototype [3] in the proposed device, the input of the second ADC 19 is connected to the second output m of the receiver 6, and the output is with the second input of the memory 10, the third input of which is connected to the output of the third ADC 20, the input of which is connected to the output of the SIS 12, the output of the memory 10 is connected to the input of the smoothing unit 18, the output of which is connected to the input of the FFT calculator 13, connected by its output to the input of the BONVP 21, the output of which is connected to the first input of the microprocessor 16, designed to identify the standards with the working vibrational portrait of the aircraft and decide on its class for the greatest degree of similarity. In this radar device, the computer is designed to calculate the spatial view of the location of the aircraft. It is assumed that the first output of the receiver is the output of its amplitude detector, and the second output of the receiver is the output of its phase detector.

A radar device for classifying vibrating aircraft with trajectory instabilities (VT) of flight in the surface layers of the atmosphere in accordance with its internal structure works as follows.

Microwave generator 1 generates powerful microwave pulses at the moments when modulating pulses are fed to its input from the output of modulator 2, the operation of which is controlled by synchronizer 3. The probe microwave pulses through AP 5 enter antenna 4 and are emitted by it in the direction of the object selected for tracking and subsequent classification. Electromagnetic waves reflected by an air object (aircraft) are picked up by antenna 4 and transmitted through AP 5 to the input of receiver 6, which includes frequency converters, frequency filters, amplifiers, amplitude and phase detectors. The detected signals from the output of the amplitude detector of the receiver 6 are fed to the inputs of the SUA 8, the first ADC 9 and the first input of the LED 7. The output of the amplitude detector is the first output of the receiver 6. In LED 7, the distance to the tracked object is measured by the delay time of the reflected signal relative to synchronization pulses, arriving at the second input of LED 7 from the output of the synchronizer 3. In SUA 8, the angular coordinates of the object are measured (elevation angle ε and azimuth β). For this, the conical scanning method must be implemented in the radar, i.e. conical deployment of XNA during rotation of the irradiator, shifted from the focus of the parabolic mirror.

Information about the angular position of the object is enclosed in the envelope of the amplitudes of the received signals and can be unambiguously read out during the scanning period. To accomplish this, in envelope 8, the envelope of the video pulses arriving at the input of the coil from the first output of receiver 6 is extracted. Error parameters are determined from the envelope by ε and β, which control the drives of coil 8, which provide a mechanical extension of antenna 4 towards the object. To do this, the mechanical connection of the first output of the SUA 8 with the input of the antenna 4 is used. From the second output of the SUA 8, signals proportional to the angular position of the escorted aircraft are fed to the second input of the computer 11, designed to calculate the spatial view of the location of the aircraft. The signals of the range to the object from the output of the LED 7 come to the first input of the PSA 11. The PSA 11, by changing the angular coordinates (ε and β) and the distance R to the object, calculates the spatial view of the object’s location (LA) γ, which comes from the output of the PSA 11 in the form of voltage to the second input of the block selection standards 15, which is part of the classification block 17.

A signal proportional to the radial speed of the object V _r from the SIS 12 is supplied to the first input of the sample selection unit 15, and the signals from the second output (from the phase detector) of the receiver 6 are fed to the input of the video signal. converting their amplitude into digital data that passes to the first input of the storage device 10.

The second ADC 19 sequentially digitizes the phase information contained in the reflected signals and transmits its digital values (from the output of the ADC 19) to the second input of the memory 10. For unambiguous removal of the amplitude and phase information in each sensing period, a coordinated processing of the signal reflected by the object is carried out. In case of coordinated processing, a complex conjugate probing signal belonging to the period of receiving the reflected signal is used as a reference function. As a result, for each sensing period, a processed quasitriangular-shaped signal received by the locator is generated, i.e. signal with peak amplitude value [9]. The moment of formation of the peak response of the reflected signal should be used to read the amplitude and phase information from the outputs of the receiver 6.

, где A_i - амплитуда i-го отраженного сигнала; ψ_i - фаза этого же сигнала.The storage device 10 is designed to subtract from the data arriving at it the phase information associated with changing the distance to the object, as well as for generating and storing arrays of quadrature components of the reflected signals, i.e. for converting and storing digital information about reflected signals. At the moment the amplitude and phase of the i-th reflected signal arrive from the outputs of the 1st and 2nd ADCs in the memory 10, a complex signal of the form is formed on the basis of this information

where A _i is the amplitude of the i-th reflected signal; ψ _i is the phase of the same signal.

, который затем преобразуется в два квадратурных сигнала Re_i=A_icosψ_{рез i} и Im_i=A_isinψ_{рез i}.The phase information of the low-frequency VP should not be distorted by the phase information associated with a change in the distance to the object. To do this, from the output of the SIS 12, the value of the measured radial velocity V _{r is} fed to the input of the third ADC 20, where it is converted into a digital code. The radial velocity of the aircraft is extracted from the amplitude modulation frequency F _{am of the} signals taken from the output of the phase detector of unit 6 by multiplying this frequency by the wavelength λ and dividing the result by 2. The digital value of the radial velocity of the object V _r comes from the output of the 3rd ADC 20 to the third input of the memory 10. In the memory 10 before storing data, the phase information associated with the change in the distance to the object is subtracted. Namely, when receiving and processing the ith reflected signal, the resulting phase is calculated using the formula ψ _{res i} = ψ _i -4iV _r T _and π / λ, where T _and is the pulse repetition period of the radar. A similar operation is known and is widely used in the formation of Doppler portraits (DP) and radar images of objects [6, 8, 10]. As a result, in each i-th sensing period in the memory 10, a complex reflected signal of the form

which is then converted into two quadrature signals Re _i = A _i cosψ _{rez i} and Im _i = A _i sinψ _{rez i} .

Digital data on the sine and cosine quadrature components ix of the reflected signals sequentially fill the cells (elements) of arrays of quadrature components formed in the memory 10. Each array has (2 ^N + Z-1), where N is a natural number in the range from 7 to 11, Z is the number of elements of a private array sample used in block 18 to find the average when smoothing.

So, the digital data for each quadrature is separately recorded in the memory cells of the storage device 10 until then, until their number is equal to (2 ^N + Z-1). The formed arrays of quadrature components of the reflected signals are supplied from the output of the memory device 10 to the smoothing unit 18. This block, using the smoothing methods known from [11, 12], forms modified arrays of quadrature components of the reflected signals. One of the simplest smoothing methods is described in [12]. The resulting quadrature arrays will contain data only on the low-frequency envelopes, and all high-frequency emissions due to fuel cells will be eliminated. When smoothing by replacing the average [12], the number of array elements decreases by Z-1. This means that in the smoothed quadrature arrays there will remain 2 ^N elements. Such a quantity of simultaneously processed data is necessary to ensure the operation of the FFT calculator 13. In this case, it is also necessary to ensure the correct sampling of the processed reflected signal so as not to lose useful information and to select a detailed analyzed spectral band of the vibrational range.

To justify the boundaries of this range, we note that on modern airplanes and helicopters, the following types of vibrations are distinguished [5, 13, 14, 15]:

a) vibrations arising from the operation of power plants (motor vibrations, including vibrations from propellers);

b) aerodynamic vibrations associated with the peculiarities of air flow around the structure of an object or its individual parts;

c) acoustic vibrations;

d) flutter-type oscillations.

In the general case, the vibration mode of the construction of objects, which is the sum of forced and natural vibrations, is determined both by the intensity and frequency spectrum of random external factors, and by the values of the corresponding transfer functions. The values of the latter depend on the spectrum of natural frequencies of the structure as a whole, its parts and elements, as well as damping coefficients. If the damping coefficients are relatively small, which is true for all modern aircraft [13], then the transfer functions will have large gain at all frequencies that match the eigenfrequencies, i.e. the vibration spectrum of a real glider will be mainly narrow-band and dependent on the design features of the object.

Studies devoted to the analysis of the propulsion systems of aircraft [14, 16] show that the largest amplitude displacements are vibrations at frequencies:

for piston engines - Ω _sq , 2Ω _sq , Ω _c , N _l Ω _c , where Ω _sq is the angular speed of rotation of the crankshaft, Ω _c is the angular speed of rotation of the screw, N _l is the number of rotor blades;

for turboprop engines - Ω _in , N _l Ω _in , Ω _p , where Ω _p - the angular velocity of rotation of the rotor;

for turbojet engines - Ω _p1 , where Ω _p1 is the angular velocity of rotation of the i-th rotor (these vibrations, according to [17, 18], occupy the range from 56 to 300 Hz, and in some cases more);

for helicopters Ω _nv , K _nv Ω _nv , where K _nv is the number of rotor blades, Ω _nv is the angular rotational speed of the rotor (these vibrations give rise to spectral responses at frequencies from 2 to 14 Hz [13]).

Studies on the aerodynamics of the flight of air objects [5, 13, 15] show that the aerodynamic vibrations prevailing in amplitude are always very close or coincide with the natural frequencies of the airframe design. The largest in amplitude of these vibrations are vibrations corresponding to the lower tones of natural vibrations. With aerodynamic vibrations, the design of the aircraft as it were is a kind of filter, emitting only those vibrations whose frequencies are in the resonance zone with its own frequency. Therefore, knowing the natural frequencies of vibration of structural elements, one can predict at which frequencies the vibrations will be maximum in amplitude. Acoustic vibrations also have frequencies close to the natural frequencies of structural elements and occupy the spectral range from 1.5 to 40 Hz [13, 15].

Thus, to classify airborne objects according to the vibration spectrum, it is necessary to analyze the frequency band in the range of ± 500 Hz. From this it follows that the sampling frequency F _d , according to the Koteliikov theorem, should be of the order of 1000 Hz. For practical reasons, you should choose a value of F _d slightly larger (for example, 1.5 kHz). Modern pulse-Doppler radar have a repetition frequency F _and up to tens or even hundreds of kilohertz. This means that it is possible to provide the required discretization of the reflected signals by converting each k-th (k = F _and / F _d ) video pulse into a digital value in an ADC.

The digitized values of 2 ^N (for example, 2048) samples of the quadrature components of the video signals form a two-dimensional (complex) data array, which comes from the output of the smoothing unit 18 to the input of the FFT computer 13. Block 13 performs an FFT operation with the data of arrays and generates a data array at its output, representing the distribution of intensities of the received reflected signals over the frequencies of the vibrational range (-500 ... + 500 Hz). A graphic representation of the modular values of the elements of such an array is usually called the spectral portrait of the object in the vibrational range or the vibrational portrait of the object. The resulting array from the output of the BPF 13 calculator is fed to the input of the block of restriction and normalization of the vibration portrait 21.

Block 21 is designed to cut out data representing the Doppler portrait of the aircraft from the generated vibrational portrait, as well as harmonics caused by the presence of a conical scanning of XNA. Numerous experiments have established that the low-frequency DP of an aircraft is distributed in the range of ± 100 Hz depending on the flight angle, VT intensity and the rate of change of the angular position of the aircraft relative to the radar [6, 8, 9, 19]. In most cases, the width of the DP does not exceed 30-40 Hz. Frequencies of scanning HNA in modern radars range from 30 to hundreds of Hz. In [20, p. 421, Fig. 17], the scanning frequency of the HNA detected by the experimental low-frequency spectrum is 37 Hz. For each radar, the scanning frequency of the XNA F _sc is known. In order for the components of the scanning modulation not to affect the quality of classification according to the VP, in block 21, at the first stage, samples representing signal amplitudes in the frequency range ± (F _ck + Δ), where Δ is half the width of the spectral emissions at frequencies, are removed from the array of the vibration portrait. F _SC If the frequency F _ck is small (up to 100 Hz) and does not exceed the frequency extent of the aircraft LA, then the samples in the frequency range ± 100 Hz should be removed.

At the second stage, in the BONWP 21, the remaining amplitudes of the components of the EP are normalized relative to the maximum. During normalization, the modules of complex spectrum amplitudes are used. After restriction (removal of non-informative readings) and normalization, the modified data array, which expresses an identification sign in the form of a “truncated” vibration portrait, comes from the output of the BONVP 21 to the input of the microprocessor 16, designed to identify the standards with the working vibration portrait of the aircraft and make a decision about it classroom for the most similarities. In block 16, the data array of the VI is compared with similar reference arrays (reference "truncated" vibrational portraits) received at the second input of the microprocessor 16 from the output of the block selection of standards 15.

The block of selection of standards 15 in accordance with the signals arriving at its inputs of the spatial view of the location γ and the radial velocity of the object V _r among the entire bank of reference arrays VP selects only that group of reference arrays that corresponds to the measured value of the angle γ and the linear flight speed of the object V = V _r / cosγ. In the selected group, the number of standards is determined by the structure of a predefined classification alphabet. When entering the second input of block 16, the reference data arrays are identified with the working VI from block 21, and the decision is made in favor of any class of objects to the greatest extent of similarity. A signal proportional to the number of the selected class comes from the output of the microprocessor 16 to the input of the BVRK 14, which indicates the appearance or name of the class (type) of the airborne object in favor of which the classification was carried out and completed.

A positive technical effect consists in the fact that when classifying by VP, only those components are used whose nature and physical nature are due to the manifestation of only the vibration effect. Due to normalization, the amplitudes of the components of the airspace become pronounced, which contributes to a more reliable classification. The remaining components belonging to the Doppler portrait, harmonics of the XNA scan process and turboprop components are excluded from the processing, which leads to an improvement in the quality of classification of objects.

Information sources

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Claims (1)

A radar device for classifying vibrating aircraft with trajectory flight instabilities in the surface layers of the atmosphere, including a sequentially connected synchronizer, modulator, microwave generator, antenna switch, receiver, the first output of which is the output of the amplitude detector, connected to a range measuring system, output which is connected to the first input of the computer, designed to calculate the spatial view of the location of the pilot of the apparatus, as well as including an antenna, an antenna control system, a speed measuring system, a first analog-to-digital converter, a storage device, a fast Fourier transform calculator, a classification unit, consisting of a unit for selecting standards, a microprocessor designed to identify the standards with a working vibrational portrait of an aircraft apparatus and making decisions about its class for the greatest degree of similarity, as well as a block for outputting classification results, and the input-output of the antenna switch is connected inen with the input-output of the antenna, the input of which is mechanically connected to the first output of the antenna control system, the second output of which is connected to the second input of the computer, the output of which is connected to the second input of the sample selection unit, the first input of which is connected to the output of the speed measurement system, the input of which is connected to the second output of the receiver, which is the output of the phase detector, while the first output of the receiver is also connected to the input of the antenna control system and the input of the first analog-to-digital converter, the output which is connected to the first input of the storage device, the output of the synchronizer is also connected to the second input of the ranging system, the output of the sample selection unit is connected to the second input of the microprocessor, the output of which is connected to the input of the output of the classification results, characterized in that the second and the third analog-to-digital converters, a smoothing unit, a unit for limiting and normalizing a vibration portrait, structurally included in the classification unit, and the ogre unit The reduction and normalization of the vibration portrait is intended for cutting out data representing the Doppler portrait of the aircraft from the generated vibration portrait, as well as harmonics caused by the presence of a conical scan of the directivity of the antenna, while the input of the second analog-to-digital converter is connected to the second output of the receiver, and the output to the second input of the storage device, the third input of which is connected to the output of the third analog-to-digital converter, the input of which is connected t with the output of the speed measuring system, the output of the storage device is connected to the input of the smoothing unit, the output of which is connected to the input of the fast Fourier transform computer, the output of which is connected to the input of the block for limiting and normalizing the vibration portrait, the output of which is connected to the first input of the microprocessor, while the storage device It is intended for subtraction of phase information associated with a change in the distance to the object from the incoming data, as well as for the formation and storage of arrays quadrature components of the reflected signals.

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