RU2549207C2 - Device for detecting hydroacoustic noise signals based on quadrature receiver - Google Patents

Abstract

FIELD: physics, acoustics.

SUBSTANCE: present invention relates to hydroacoustics and specifically to devices for detecting hydroacoustic noise signals in the form of discrete components on the background of additive noise. The result is achieved due to use of quadrature detection in each frequency channel of a passive broadband system.

EFFECT: high noise-immunity of a detector for detecting hydroacoustic noise signals in form of discrete components.

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Description

The present invention relates to the field of hydroacoustics, and in particular to devices for detecting broadband noise signals (with a power spectral density in the form of individual discrete components or their scale) against the background of additive interference.

As is known [1-4], the main task of the receiving part of the signal detection system is to decide on the presence or absence of a useful signal from the object in the observed input process. This is a difficult task, presenting the highest requirements to the receiver, because Signal detection typically occurs with minimal signal-to-noise ratios (SIR). The decision on the presence of a signal is made when the response of the receiver exceeds the set threshold, selected on the basis of one of the statistical criteria for the given probabilities of correct detection and false alarm.

To ensure maximum response with a fixed OSB at the input of the system, the receiver circuit should be optimal.

In practice, the task of detecting a noise (random) signal from a noisy underwater object against a background of interference is of particular interest.

Currently, to solve this problem, the most widely used are the so-called passive broadband and narrowband sonar systems [1, 5, 6].

When using a passive broadband system, the fact that the signal from the object is usually a typical broadband random process, the duration of which is limited only by the relative position and relative movement of the object and the receiver, is taken into account. In this case, only certain statistical characteristics of the signal and interference are known (for example, the shape of the spectral density of the signal, its approximate duration, as well as the shape of the spectral density of the interference, which is not necessarily white noise).

However, the spectrum of noise emitted by various objects, along with the broadband component, can contain narrow-band discrete components [1, 5-7].

The known method for detecting broadband noise with discrete components of the PSD and the device implementing it, in fact, are a multi-channel energy receiver (prototype) [1, p. 351-352]. This method is a sequential operation: multi-channel narrow-band bandpass filtering (for the formation of individual frequency channels), quadratic detection, integration and comparison with a threshold (in each frequency channel).

A device (prototype) [1, p. 351-352] that implements the specified method for detecting narrowband noise, is shown in figure 1, where:

block 1 - analog-to-digital Converter (ADC);

block 2 - recirculator;

blocks 3.1-3.M - a set (“comb”) of digital narrow-band bandpass filters (UPF), with the same bandwidth and different center frequencies (with a uniform frequency step equal to the bandwidth of one filter);

blocks 4.1-4.M - quadrators;

blocks 5.1-5.M - integrators;

block 6 - M-channel threshold device.

The principle of operation of this device is as follows. The input of the device receives the implementation of the input process

where: s (t) is the detected narrowband noise signal,

n (t) is the additive interference in the form of normal white noise,

.which is fed to the ADC input (block 1) with a sampling rate that satisfies the requirements of Kotelnikov’s theorem: $$f_{\partial }=\frac{\mathrm{one}}{\Delta t_{\partial }}\ge 2f_{\mathrm{at}}$$

.

From the output of the ADC (block 1), discrete, the samples go to the input of the recirculator (block 2), where the current discrete sample x (n) of length N samples is generated and updated with each new sample.

The generated current discrete sample of the input process x (n) is fed simultaneously to the inputs of M digital narrow-band filters (blocks 3.1-3.M) (M-channel comb UPF), where M of individual frequency channels are formed.

The formed (filtered) narrow-band noise processes go to the inputs of the quadrators (blocks 4.1-4.M), from the outputs of which squared narrow-band signals go to the inputs of the integrators (blocks 5.1-5.M). The integration time (or accumulation) of narrow-band signals is usually chosen to be equal to the inverse proportion to the UPF bandwidth [1], and providing potential frequency resolution for this spectral analysis method (filtering method).

From the outputs of the integrators, the selected responses are fed to the input of the M-channel threshold device (block 6), the output of which is the output of the device.

Thus, as the main elements of this passive narrowband system, quadratic detectors and integrators are used that implement the output statistics [1]:

where x (t) is the input process, which is a mixture of the noise signal from the object and interference;

T is the integration time.

Thus, to obtain sufficient; For statistics, it is necessary to have a quadratic detector, the output voltage of which is proportional to the square of the input, and an integrator.

The noise immunity of the receiver based on a quadratic detector, called the "energy receiver" (since statistics is equivalent to the total energy of the input process), is the lower boundary of all optimal receivers.

For other a priori data on the properties of signals and interference, the noise immunity of the optimal receiver will occupy an intermediate position between it and the ideal correlator (matched filter), that is, it will have greater noise immunity.

As such a priori data on the properties of the noise signal from an object, one can use data on narrow-band discrete signal components (the so-called discrete components), which are actually a set of elementary continuous sinusoidal (monochromatic) signals of the corresponding frequency. In this case, we can talk about solving the problem of detecting a polyharmonic signal against a background of interference.

To solve this problem, the simplest hypothesis is the assumption of the determinism of each signal component in the bands of the corresponding narrow-band filters. In this case, a deterministic signal is understood to mean one whose all parameters are known at reception, and the uncertainty is contained only in its presence or absence and is associated with the masking effect of interference. The receiver of a fully known deterministic signal (ideal correlator) is optimal in this case, it provides the maximum possible, i.e. potential noise immunity, which is theoretically impossible to surpass.

However, under real conditions of reception of discrete components of the noise signal against the background of interference, the determinism of the useful signal cannot be discussed, since (at least) the initial phase of the signal in the processed sample of the input process, limited in time, is unknown. In this case, the expression for the narrow-band process s (t) (discrete signal component) can be written as

where A is the signal amplitude (an independent random variable distributed according to Rayleigh law);

φ is the phase of the signal (an independent random variable distributed uniformly over the interval [-π; π]).

In this case, it is proposed to use the optimal signal receiver with an unknown initial phase (quadrature detector) [2-4] (analog) as a detecting element (optimal receiver) of a passive narrow-band system that implements statistics:

where X _C and X _S are the cosine and sine components of the envelope of the output oscillation of the correlation receiver, respectively:

where T is the integration time.

The decision on the presence or absence of a signal is made depending on the inequality

where: h is the threshold level.

The scheme that implements obtaining sufficient statistics (4) is presented in figure 2,

Where

blocks 7.1, 7.2 - multipliers;

block 8 - read-only memory (ROM), from the outputs of which digital signals in the form of cosine and sine components of the same center frequency are fed to the inputs of the multipliers;

blocks 5.1, 5.2 - integrators;

blocks 4.1, 4.2 - quadrators;

block 9 - adder;

block 10 is a square root calculator.

Two channels of the quadrature receiver allow to obtain the values of X _C and X _S. The subsequent nonlinear transformation of the output oscillations of these channels will give the value Λ (X). In this case, the quadrature frequencies correspond to the central band of the corresponding input UPF.

A comparison of the noise immunity of the quadrature receiver and the correlator shows that there are losses in the SIR, which are a fee for not knowing the phase, but these losses are small and amount to 1.5 dB [8].

In the practical implementation of the proposed detector of polyharmonic signals, a number of fundamental questions arise.

First, it is necessary to determine the frequency characteristics of narrow-band filters (UPF _m ) - the passband of the filters (Δf _m ) and their center frequencies (f _m ).

The definition of the above characteristics is based on the need to ensure a constant filter duty cycle (the ratio of the filter bandwidth to its center frequency) in the entire frequency range, namely

After elementary transformations, one can obtain the defining relations:

The number of narrow-band filters in the comb for the total frequency band ΔF will be

Secondly, it is necessary to take into account that the analysis (integration) time in the band of each filter will be determined by the expression

Obviously, in the case of accumulation of responses from several detector channels (summing of the output processes), agreement on the analysis time is necessary, i.e. the introduction of time delays at the outputs of the channels before the operation of summation.

The introduction of the response accumulation operation is due to the need to increase the efficiency of detecting the scale of a polyharmonic signal and taking into account the possible influence of the Doppler effect during mutual movement of the receiver and the signal source.

Obviously, for a comb of M filters, the delay parameters can be defined as

.

.

The proposed device for detecting broadband noise hydroacoustic signals based on a quadrature receiver is shown in figure 3, where:

block 1 - analog-to-digital Converter (ADC);

block 2 - recirculator;

blocks 3.1-3.M - a set of digital narrow-band bandpass filters (UPF), covering the expected frequency range, with different bandwidths and different center frequencies, but with a constant filter duty cycle (the ratio of the filter band to its center frequency) in the entire frequency range, namely

;

;

blocks 7.1-7.2M - multipliers;

block 8 - ROM;

blocks 5.1-5.2M - integrators;

blocks 4.1-4.2M - quadrators;

blocks 9.1-9.M - adders;

blocks 10.1-10.M - square root calculators;

blocks 11.1-11.M - delay devices with delay parameters

;

;

block 9 - adder;

block 6 - threshold device;

block 12 is a control device.

.The principle of operation of the device is as follows. The input of the device receives the implementation of the input process x (t), which is fed to the ADC input (block 1) with a sampling frequency that satisfies the requirements of Kotelnikov's theorem: $$f_{\partial }=\frac{\mathrm{one}}{\Delta t_{\partial }}\ge 2f_{\mathrm{at}}$$

.

From the ADC output (block 1), discrete samples go to the recirculator input (block 2), where the current discrete sample x (n) of length N samples is generated and updated with each new sample.

The generated current discrete sample of the input process x (n) is supplied simultaneously to the inputs of M narrow-band filters (blocks 3.1-3.M).

From the outputs of M narrow-band filters (blocks 3.1-3.M), the corresponding narrow-band processes simultaneously arrive at the first inputs of M pairs of multipliers (blocks 7.1-7.2M), from the outputs of which the results of multiplication go to the inputs of M pairs of integrators (blocks 5.1-5.2M ) The integration time in the band of each filter is determined by the expression

.

.

From the ROM (block 8), the second inputs of M pairs of multipliers (blocks 7.1-7.2M) receive M pairs of sine and cosine components (monochromatic) digital signals with frequencies corresponding to the center frequencies of the UPF f _m .

From the outputs of M pairs of integrators (blocks 5.1-5.2 M), the results of integration are fed to the inputs of M pairs of quadrators (blocks 4.1-4.2 M), from the outputs of which the squares of responses are coupled to the inputs of the M adders (blocks 9.1-9.M), from the outputs whose summation results go to the inputs of M square root calculators (blocks 10.1-10.M), the outputs of which the calculation results go to the inputs of M delay devices (blocks 11.1-11.M).

The delay parameters in each frequency channel are determined by the relation

.

.

From the outputs of the M delay devices (blocks 11.1-11.M), the responses arrive at the inputs of the adder (block 9), from the output of which the summation result is fed to the input of the threshold device (block 6), the output of which is the output of the device.

The control device (block 12) synchronizes the operation of an analog-to-digital converter (block 1), a recirculator (block 2), a ROM (block 8) and a threshold device (block 6).

The achieved gain in noise immunity of the proposed detector of broadband noise signals based on quadrature detection (and, accordingly, in the range of the hydroacoustic noise detection system) compared to the prototype (device for detecting broadband noise based on quadratic detection or an energy receiver) is achieved by using a larger amount of a priori information about the detected useful signal.

List of sources used

1. Burdick B.C. Analysis of sonar systems. L .: Shipbuilding, 1988, 392 p. (prototype, p. 351-352).

2. Tikhonov V.I. Optimum signal reception. M: Radio and communications, 1983, 320 p. (Analogue, p. 80-87).

3. Van Tris G. Theory of detection, estimates and modulation, vol. 1, M .: Sov. Radio, 1972, 744 p.

4. Van Tris G. Theory of detection, estimates and modulation, vol. 3, M .: Sov. Radio 1977, 661 pp.

5. Urik R.J. Basics of sonar. L .: Shipbuilding, 1978, 446 p.

6. Zaraysky V.A., Tyurin A.M. The theory of sonar. L .: VMA, 1975, 604 p.

7. Bolgov V.M., Plakhov D.D., Yakovlev V.E. Acoustic noise and interference on ships. L .: Shipbuilding, 1984, 192 p.

8. Olshevsky V.V. Statistical methods in sonar. L .: Shipbuilding, 1983, 280 p.

Claims (1)

A device for detecting noise hydroacoustic signals based on a quadrature receiver, comprising: an analog-to-digital converter, the input of which is supplied with an input signal, and the output of which is connected to the input of the recirculator, the output of which is connected to the inputs Μ of narrow-band filters, characterized in that the outputs Μ of narrow-band filters are connected with the first inputs Μ pairs of multipliers, the outputs of which are connected to the inputs Μ pairs of integrators, the outputs of which are connected to the inputs Μ pairs of quadrators, the outputs of which are paired with input Μ rows adders, whose outputs are connected to inputs Μ square root calculators whose outputs are connected to inputs Μ delay units whose outputs are connected to inputs Μ adder whose output is connected to the input of the threshold device, whose output is the output of the apparatus; 2M outputs of read-only memory connected to the second inputs Μ pairs of multipliers; the outputs of the control device are connected to the control inputs of the analog-to-digital converter, recirculator, read-only memory and threshold device.

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