Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2000-07-07
2002-05-28
Bui, Bryan (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C702S075000, C702S077000, C455S067700
Reexamination Certificate
active
06397154
ABSTRACT:
FIELD OF THE INVENTION
The present invention is directed toward an apparatus and method for detecting the presence of concealed eavesdropping devices. More particularly, the present invention relates to a method and apparatus for correlating a detected signal with a reference signal in order to determine the presence of a concealed eavesdropping device.
BACKGROUND OF THE INVENTION
Many devices and methods are available today for detecting the presence of concealed surveillance device. One such method of attempting to detect a surveillance device is to detect the transmitted signals from an eavesdropping device present in a location and compare a demodulated transmitted signal to a reference signal, which is related to the ambient audio in the environment. If there is a strong correlation between the reference signal and the detected signal, there is a good probability that the detected signal is the result of a hidden eavesdropping device. Thus, a strong correlation between the two signals typically indicates the presence of a covert eavesdropping device that is transmitting a representation of the audio in a room to a remote location. The method of transmission from the eavesdropping device may include a wide variety of transmission medium such as electromagnetic radiation (from radio frequency broadcasts to optical transmission media such as infrared, visible, ultraviolet, LASER, etc.) to hardwired methods (such as dedicated lines, telephone lines, power lines, or any other existing wiring in an environment).
There are prior art methods for performing eavesdropping device detection. One such method of detecting an eavesdropping device is disclosed in U.S. Pat. No. 5,241,699 which is assigned to Research Electronics, Inc. and which is hereby incorporated by reference. This method relies on a phase correlator. The main drawback of a phase correlator is that it does not consider the phase distortions and time delays that result from the speed of sound and echoes from within the environment. Furthermore, it has the drawback that the phase correlator works very well for a continuous audio tone with a constant phase, but works poorly if the audio source has a very wide bandwidth with little continuous tone content.
There are also some prior art correlation methods that rely on basic mathematical cross-correlation and auto-correlation methods. In German patent application No. 24 28 299 February 1976 (Wächtler), there is disclosed a system for detecting eavesdropping transmitters using a cross correlation between a reference audio signal and a demodulated version of a detected transmission. In U.S. Pat. No. 5,717,656 February 1998 (Dourbal) and Russian patent No. 94025549/09 August 1995 (Dourbal), there is disclosed a method for detecting eavesdropping transmitters using cross correlation and autocorrelation functions. These patents by Dourbal (US and Russian) also include a method for detecting the range to the eavesdropping device. However, these prior art correlation methods suffer from a number of drawbacks. For example, the prior art devices utilize basic cross-correlation to determine the correlation between the reference signal and the detected signal. However, basic cross-correlation only provides a resulting correlation number. This number simply indicates that the signals are, or are not, correlated. Thus, basic cross-correlation and auto-correlation techniques do not provide robust resultant information about the relationship between the signals because these prior art correlation techniques do not work well in large rooms with large time delays and phase distortions resulting from echoes. Furthermore, the prior art correlation techniques that incorporate a ranging function or locating function have some drawbacks. First of all, the prior art basically relies on measuring the timed response of the initiation of a known sound source and comparing the time of arrival difference between the reference signal and the intercept signal. This method of range determination also does not work well in large rooms with large time delays and phase distortions resulting from echoes. Therefore, the cross-correlation of the prior art is deficient in a number of respects. Furthermore, all known prior art correlation methods fail to provide the ability to evaluate the frequency response of the intercepted signal and/or the reference audio signal and to automatically introduce a filtering capability into the correlation process to improve upon the correlation data and range finding capabilities of the process.
Yet another problem with prior art devices is that the correlation methods utilized are highly dependent upon unpredictable signal and noise amplitude levels in the room. Thus, it may be necessary to introduce particular types of reference audio into the room in order for the prior art correlation methods to provide any type of useful results. However, producing unusual noises in the room may tip off a third party that is monitoring the room that a detection attempt is being made. This information may result in the third party turning off the surveillance device and frustrating any attempts to locate the device. Thus, the prior art correlation methods create a risk of detection by alerting a third party operating the surveillance device.
Therefore, in view of the above discussed deficiencies in the prior art, what is needed is an advanced correlation method and apparatus which require few mathematical calculations to implement. The invention should not require the introduction of an easily detectable noise source into the room to be scanned. In addition, the correlation method and apparatus should allow the user to determine the surveillance device's location.
SUMMARY OF THE INVENTION
The present invention overcomes the above discussed deficiencies of the prior art by providing a new correlation method which is implemented using discrete Fourier transforms. One skilled in the art will appreciate that discrete Fourier transforms are utilized when dealing with sampled data. While there are many discrete Fourier transform algorithms, the preferred embodiment of the invention utilizes a Complex Fast Fourier Transform to minimize the required calculations. In addition, the data sets calculated are preferably normalized after each Fourier transform process to ensure that the amplitude levels of the data sets do not affect the resulting correlation data. This process is referred to as Fast Correlation.
In particular, the preferred embodiment of the present invention is directed toward a method for detecting the presence of an electronic eavesdropping device that is generating a transmission signal corresponding to sounds in an environment. In accordance with the method, ambient sounds in the environment are detected. Alternatively, a sound source may be generated to produce ambient sounds that would be non-alerting to any third party that may be eavesdropping on the environment. A reference signal corresponding to the ambient sounds in the environment is then generated. An intercept signal corresponding to a detected transmission signal present in the environment is also generated. The reference signal and the intercept signal are sampled to produce sampled reference signal data and sampled intercept signal data. The reference signal is then compared to the intercept signal to determine if an electronic eavesdropping device is present in the environment by performing a fast correlation process on the sampled data.
The preferred embodiment of the invention utilizes a fast correlation process that includes the taking of a Fourier Transform of the sampled reference signal data and an Inverse Fourier Transform of the sampled intercept signal data. The Inverse Fourier Transform of the sampled intercept signal data and the Fourier Transform of the sampled reference data are multiplied to produce product data. The resulting product data is a frequency representation of the correlation of the reference signal and the intercept signal. This product is then filtered by multiplying the product by
Barsumian Bruce R.
Jones Thomas H.
Bui Bryan
Luedeka Neely & Graham P.C.
Research Electronics International
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