WO2020016666A1

WO2020016666A1 - Method for detecing anomalies in an electromagnetic spectrum

Info

Publication number: WO2020016666A1
Application number: PCT/IB2019/054232
Authority: WO
Inventors: Giovanni MARINO
Original assignee: Ssddm Limited
Priority date: 2018-07-18
Filing date: 2019-05-22
Publication date: 2020-01-23

Abstract

The present invention relates to a method for automatically detecting anomalies of the electromagnetic spectrum associated to an environment of interest, comprising four main steps: - acquiring randomly in time the spectrum of frequencies of interest; performing a test of order statistics of the spectrum with respect to a predetermined reference spectrum; - updating the counters measuring the number of changes detected with respect to the reference spectrum; - performing a test on the counters to verify if the detected changes correspond to non-impulsive emissions.

Description

METHOD FOR DETECING ANOMALIES IN AN ELECTROMAGNETIC

SPECTRUM

DESCRIPTION

Technical field of the invention

The present invention relates to a method for the automatic detection of anomalies existing in the electromagnetic spectrum caused by unwished external perturbations, by using passive electronic systems.

In particular, the invention allows to detect changes in the electromagnetic spectrum associated to a determined environment, wherein other electronic devices can be, or cannot be, present to detect potential external interferences.

Background

Nowadays, the electromagnetic waves constitute one of the most intensively exploited means as they allow to transmit information without using wired connections, even in long distances. The exploitation of the electromagnetic signals is by now unavoidable within the most different technologies, with particular reference to the electronic, biomedical and above all telecommunication field.

The introduction of new services and devices which are based upon the transmission of data by means of electromagnetic waves, together with the increased use in the fields wherein they have been used already for decades, has produced an overcrowding of the available frequencies, by making their management very difficult. Such overcrowding of frequencies has created new problems, in particular in allocating frequencies for new proposed services, such as monitoring the correct allocation of the signals generated by new devices.

Moreover, manifestations of electromagnetic perturbations are more and more common, caused by the mutual interference of electromagnetic apparatuses, in particular by low cost radiofrequency systems which often are not devised so as to meet the criteria of electromagnetic compatibility.

In fact, the change in the electromagnetic spectrum of a device can take place for several reasons, one thereof is the not fulfilment of the criteria of electromagnetic compatibility ( ElectroMagnetic Compatibility, EMC). Additional causes can be linked to phenomena of electromagnetic interference ( Electromagnetic Interference, EMI), as well as the use of interception/disturbance means of the telecommunication systems.

The effects of the unwished changes in the electromagnetic spectrum of devices used in industrial, scientific and medical activities can be varied and dangerous. In the enclosed Figure 1 , exemplifying graphs are illustrated showing anomalies in the radio emissions caused by single electromagnetic pulses having short time duration (such as for example those characteristic of the so-called Remote Keyless Systems, RKS) and by electromagnetic signals having prolonged duration.

Certainly, the unwished perturbation of the electromagnetic spectrum of biomedical apparatuses is one among those involving the worst risks, as the correct operation of such apparatuses is necessary to guarantee the health state of whoever benefits therefrom. In this sense, the non-operation of the apparatus can be determined or defects in monitoring the physiological parameters can occur, by causing permanent damages to the patient or by resulting even lethal.

By going into details, a class of biomedical devices highly sensible to the electromagnetic interferences is constituted by the pacemakers ( Implantable Cardioverter Defibrillator, ICD), which base their own operation on the capability of estimating the cardiac frequency and acting suitably in case there are anomalies. The ICD devices implement the detection of electric pulses generated by the cardiac system, therefore the presence of external electromagnetic fields can invalidate the correct operation thereof.

Moreover, interactions can occur between electromagnetic devices sharing the same ISM use band ( Industrial , Scientific and Medical, name assigned by the International Union of Telecommunications to a set of portions of the electromagnetic spectrum reserved to not commercial radiocommunication applications, but applications for industrial, scientific and medical use). A classic example is that of sharing in the band ranging from 433,050MHz and 434,790MHz, intended to the amateur communications (that is by means of the common walkie-talkie) and for the remote systems for autos (RKS).

An additional negative consequence associated to the above-discussed problems is the safety vulnerability of telecommunication systems, and therefore the potential privacy violation of data of groups of people/organizations handled by such systems. On this regard, a particularly sensitive problem consists in detecting the presence of, often not legal, systems for recording and transmitting via radio sensitive data, using (even not legally) radio frequencies and which can interfere with other apparatuses.

US 2003/064721 A1 describes a method for analysing the environment electromagnetic field based upon statistical properties of the magnetic field measured in time, for different frequencies.

Summary of the invention

The technical problem placed and solved by the present invention is then to succeed in determining anomalous variations in the electromagnetic spectrum associated to a determined environment.

The above-mentioned problem is solved by a method according to the independent claim 1.

Preferred features of the present invention are set forth in the depending claims. The proposed method provides to perform automatically the monitoring of the electromagnetic radiation (electromagnetic signal) associated to an environment or geographic area, and to detect the possibly existing anomalies. For example, the electromagnetic spectrum existing in a room can be monitored. If at a certain point a device is switched-on which erroneously emits electromagnetic waves in a band of interest, by means of the present invention it is possible to detect the presence thereof.

To this purpose, the system provides to perform at first the determination of a spectrum of the electromagnetic radiation existing in the environment to be monitored, with reference to specific frequencies or bands of frequencies of interest.

Advantageously, the method provides to discriminate the anomalies detected with respect to a reference spectrum based upon their entity and duration. In fact, single electromagnetic pulses, that is disturbance signals having short time duration, are not such as to influence negatively the behaviours of possible electromagnetic systems existing in the environment, nor they are indicative of possible presence of unwished devices. On the contrary, the disturbance signals having sufficiently long duration can result to be of particular interest, as they can represent an unwished transmission of data, or for example they can influence in time the results of the detections of electronic/electromedical instruments and even prevent the operation thereof.

According to an additional aspect of the invention, the proposed method allows to implement a monitoring of the electromagnetic radiation of an environment continuously in time, to produce an alert signal should an anomaly, which is considered dangerous, be detected.

Other advantages, features and use modes of the present invention will result evident from the following detailed description of some embodiments, shown by way of example and not for limitative purposes. Brief description of the figures

The enclosed Figures will be referred to, wherein:

- Figure 1 shows examples of taxonomy related to two types of electromagnetic emissions, wherein there are anomalies; - Figure 2 shows a flow chart related to a first preferred embodiment of a method according to the present invention;

- Figure 3 shows a flow chart related to a second preferred embodiment of a method according to the present invention;

- Figure 4 shows a flow chart related to a third preferred embodiment of a method according to the present invention; and

- Figure 5 shows a flow chart related to a fourth preferred embodiment of a method according to the present invention.

The above-mentioned Figures are to be meant exclusively by way of example and not for limitative purposes.

Detailed description of preferred embodiments

A first preferred embodiment of a method according to the present invention is exemplified by the block diagram of Figure 2.

The method first of all comprises a first step of determining a reference electromagnetic spectrum ( background map) of the area of interest. For example, the background map represents the electromagnetic spectrum existing in the room or office wherein the device is installed.

The reference electromagnetic spectrum corresponds to the spectrum of the electromagnetic radiation which the devices, existing in the area of interest, emit under nominal conditions, that is in absence of anomalies induced by external perturbations, and therefore, once determined, it cannot be changed.

In fact, since there are frequency bands used by several already operating services for example mobile phones or FM radios, it is known in advance which signals are present in the monitored environment. Therefore, it is possible to verify if in time there are electromagnetic emissions which are not present in the background map, as it will be described more in details hereinafter.

The reference spectrum is acquired relatively to frequency bands or single frequencies of interest, thereof one wishes to obtain the detection of possible anomalies.

Secondly, the acquisition is made in the time domain of the real operational electromagnetic radiation associated to the environment of interest, that is a sampling is made of the radiation really emitted in the environment of interest in a time interval of predetermined duration. In other words, the spectrum associated to the monitored environment is acquired in time, at determined instants. In the specific case, it is to be meant that the sampling takes place on the electromagnetic signal and thereon the spectrum is calculated. Subsequently, a selection in time takes place of which spectrum is, or is not, to be analysed, that is the sampling, as it will be further discussed later.

For each sample, that is for each acquisition made by means of the sampling, the operational electromagnetic spectrum is determined, related to determined frequencies of interest. The signals in the bands of interest are always acquired, whereas the spectrum of interest is selected in a given time instant. The acquisition of the spectra of interest in time can take place according to different sampling modes, as it will be explained hereinafter.

Subsequently, for each frequency of interest, it is possible calculating the order statistics of the operational electromagnetic spectrum with respect to the reference electromagnetic spectrum. Such order statistics is compared to a first threshold value, predetermined depending upon the specific monitored environment and the electromagnetic radiation, to exclude that the noise is meant as disturbance signal, and then not relevant to the purpose of the present method. In other words, such comparison is required to avoid to detect false positives. Still, by means of a suitable counter the number of times is counted in which said order statistics is greater than or equal to an additional predetermined threshold value.

When on the considered time interval in which the sampling is performed, for at least one of the frequencies of interest, the value of such number of times is higher than the additional predetermined threshold value, the presence of a non- impulsive perturbation is detected. In this case, the automatic generation of a corresponding alarm signal can be further provided.

Once ended the sampling time interval, the method provides to set to zero the counter and to repeat the above-described passages, to monitor the operational radiation on a subsequent time interval, which preferably has the same duration as the previous one.

In substance, the acquisition of the operational radiation in the time domain is required to detect the continuous interferences in time, or however the interferences having a higher duration than a predetermined threshold value depending upon the characteristic parameters of the monitored environment, and to exclude, instead, the transitory or impulsive interferences.

With reference to the test of order statistics of the spectrum of interest determined by the sampling, with respect to the reference spectrum the definition of order statistics is provided hereinafter. Let xp n be independent replications of an aleatory experiment (also called statistical sample). Then the aleatory variables that is the same n independent replications xp, arranged in

increasing order, represent the order statistics corresponding (or associated) to the sample.

The order statistics are among the most important tools of the not parametric and interference statistics. Special cases of the order statistics are those of the minimum, maximum and sample range (that is:

In particular, the probability density of the order statistics of the latter is defined as:

wherein and respectively, are the function of cumulative probability and

the probability density of the aleatory variables of the experiment.

By integrating (1 ) the probability is obtained that all order statistics are present in the range R. The exponential distribution is particularly interesting, as it has the property of lack in memory (that is memoryless property) and moreover it can model other distributions which have an exponential asymptotic behaviour.

Therefore, by taking into consideration a general exponential distribution with scale parameter l (that is scale parameter) becomes:

After such first test of order statistics, it is provided to count the number of variations of the spectrum of interest detected with respect to the reference spectrum, by using counters which are correspondingly updated. The counted variations are preferably those having a higher entity than a predetermined threshold value, with the purpose of excluding all variations relating to the noise. At last, a second test on the counters is performed, to verify if the counted variations correspond to signals or non-impulsive external emissions.

Such second test provides to count the number of times in which, in the sampling time interval for the acquisition of spectra, the changes in order statistics have exceeded the threshold value. The operation is useful to verify if in a time interval there are perturbations caused by signals or repeated and non-impulsive external emissions.

The above-described steps are required to detect and discriminate the anomalies detected both in the time domain and in the frequency domain. The acquisition in the frequency domain is required to determine at which frequency the anomaly takes place, and if the latter is an anomaly of interest or an implementation of the noise process.

In substance, a double filtering in the time domain and in the frequency domain is implemented to remove the impulsive emissions and the thermal noise.

A second preferred embodiment of the method according to the present invention is shown in Figure 3. Although not described, reference is made to the previous description related to the embodiment of Figure 2. The preferred embodiment of Figure 3 provides to perform the sampling of the operational electromagnetic radiation (that is selection of the electromagnetic spectrum under examination) according to a random mode (blocks designated with the numeral references 1 , 2 and 3). In particular, K acquisition indexes for /= 1 are generated. The coefficients K remain fixed until / reaches its maximum (that is the maximum number of time instants set to discriminate the impulsive emissions from the continuous ones). The embodiment of Figure 3 shows the continuous case if 3K indexes I are taken.

The first acquisition step in the time domain of the operational electromagnetic radiation, to determine the spectrum of the frequencies of interest, is made in particular according to a continuous mode (block 1 ).

Even the vectors required to the algorithm operation, which constitute the background map, are initialized:

obtained according to the already described modes (that is it is fixed, stored in a file and used for the comparison) for each f of the spectrum of interest, and the vector of frequencies of the spectrum under examination: for each examined frequency f of the

spectrum of interest. Subsequently, it is possible to provide a step for verifying if the frequencies under examination have higher nominal values (in the reference spectrum) than a determined threshold value a, otherwise they are excluded from the subsequent analyses (block 4). Such additional check is useful to avoid the detection of false positives, due to scale operations in case performed on the spectrum. In other words, the parameter a can be selected to ease the comparison procedures between the background map and the spectrum under examination independently from the adopted hardware.

The recursive portion of the method is shown hereinafter, explained in details in the following discussion.

The recursive portion of the method consists in repeating some operations (blocks designated in Figure 3 with the numeral references 4, 5 and 6) for a number of times equal to at least three times the cardinality of the set of the random acquisition indexes. This selection is made to guarantee that the acquisition variable / assumes at least k times a value in the set

. Once acquired a spectrum and verified that the acquisition index is

it is analysed if the probability of the range between the cell of interest ( under investigation)

and the analogous one of the background map (the

parameter

is introduced for scale reasons, thus by making the algorithm independent from the hardware used to acquire data) is, or is not, higher than a predetermined threshold (that is b is the calculation of the order statistics).

As the samples under examination are only two in (2), in the example case n=2 was set. Conceptually, this means to verify which is the probability that the range is quite wide so that x_ui is not the implementation of a thermal noise, but

actually a signal.

However, it is to be meant that not necessarily the algorithm requires to have a so defined threshold: there could be infinite criteria to define the threshold of the order statistics. As far as the threshold is concerned, it depends upon the scale factor of the exponential distribution modelling the thermal noise (l) and upon the signal-noise ratio (SNR) which is considered as minimum to detect perturbation ( change detection). Moreover, the signal-noise ratio even quantifies the maximum range with respect thereto one wishes to guarantee the monitoring service coverage. The counter is updated (block 7) if for a frequency the order statistics of the range sample exceeds the threshold, otherwise it is reset. This last operation is useful to guarantee that the detection of the signals has non- impulsive nature. Once finished the analysis of the spectra, it is checked (block 8) that the counter has a number of values equal at least to k, thus by guaranteeing the presence of a change detection of a non-impulsive emission.

With reference to Figure 4, an additional variant of the method according to the present invention is described hereinafter. A difference between the embodiment of Figure 3 and that of Figure 4 lies in the fact that in the embodiment of Figure 3 the random sampling takes place in the selection of the acquired spectrum: that is the acquisition process takes place continuously, as if there was the situation of Figure 1 - case of non-impulsive response - and the selection process is due to the generation of the acquisition indexes K: if the index /,==i-th iteration of the algorithm, then one proceeds with the calculation and the order statistics test, otherwise not.

The additional embodiment of the method provides a different mode for performing the sampling randomly in time. In fact, the block diagram shows that the implementation of the random sampling provides to generate the indexes {/₁ ...,4} as expected random of the processing unit, as it takes place for example in the waiting time for the re-transmission for protocols of known type, such as Aloha protocol.

The acquisition is then provided according to the above-mentioned mode of random sampling of the acquisition index /, which shows the index of the current random acquisition of the spectrum of interest. By going in more details, the sampling is performed by means of a random generation of k e N (set of Natural numbers) acquisition indexes

Subsequently, the counters

for each f of the spectrum of interest are initialized. hereinafter the recursive portion of the additional embodiment of the method of Figure 4 is shown.

The third variant is shown in Figure 5 and it represents a variant of the version shown in Figure 3. It differs from the previous one for the simple fact that the selection of the sampling instants is fixed in advance (that is the generation of the indexes is fixed only once and it is valid forever, with consequent vulnerability of the system). As to the additional aspects, the algorithm has an equal recursion to that of the embodiments shown in Figures 3 and 4.

The present invention has been sofar described with reference to preferred embodiments. It is to be meant that other embodiments belonging to the same inventive core may exist, as defined by the protective scope of the here below reported claims.

Claims

1. A method of monitoring the operational electromagnetic spectrum of electromagnetic radiations associated to an environment of interest, to which environment of interest a reference electromagnetic spectrum is associated, for the detection of a non-impulsive perturbation of said electromagnetic spectrum, said method comprising the following steps: a) performing the sampling of such electromagnetic radiations in a time interval of predetermined duration, with reference to specific frequencies of interest; for each sample: b) determining the operational electromagnetic spectrum related to said sample, and for each frequency of interest: c) calculating the order statistics of said electromagnetic spectrum with respect to the reference electromagnetic spectrum; d) comparing said order statistics with a first predetermined threshold value; and e) counting the number of times wherein said order statistics is greater than or equal to said first predetermined threshold value, said non-impulsive perturbation being detected if, for at least one of the frequencies of interest, the value of said number of times is greater than a second predetermined threshold value (K).

2. The method according to claim 1 , wherein said sampling is performed randomly.

3. The method according to claim 1 , wherein said sampling is performed at predetermined instants of said time interval.

4. The method according to anyone of the preceding claims, wherein said order statistics is calculated exclusively with referent to frequencies of interest whose value of reference electromagnetic spectrum is greater than the respective value of the background map and than an additional predetermined threshold value (a).

5. The method according to anyone of the preceding claims, comprising the additional step of automatically generating an alarm signal if a non-impulsive perturbation is detected.