Granted Patent B2

US 10,575,274 · App. 16/295,691 · Granted Feb 25, 2020

Inventors: Ronald C. Dzierwa (Baltimore, MD); Daniel Carbajal (Severna Park, MD); David William Kleinbeck (Lees Summit, MO)

Assignee: DIGITAL GLOBAL SYSTEMS, INC.

H04W64/00H04B17/23H04B17/26H04B17/318H04B17/373H04L27/0006H04L27/0012H04L27/265H04W16/14

Abstract

Claims (52)

1. A method for automatic signal detection in a radio-frequency (RF) environment, comprising:

learning the RF environment in a learning period based on statistical learning techniques, thereby creating learning data including power level measurements of the RF environment;

forming a knowledge map of the RF environment based on the power level measurements of the RF environment;

scrubbing a real-time spectral sweep against the knowledge map;

calculating a first derivative of the power level measurements and a second derivative of the power level measurements;

selecting most prominent derivatives of the first derivative and the second derivative;

performing a squaring function on the most prominent derivatives;

detecting at least one signal in the RF environment based on matched positive and negative gradients;

averaging the real-time spectral sweep, removing areas identified by the matched positive and negative gradients, and connecting points between removed areas to determine a baseline;

subtracting the baseline from the real-time spectral sweep to reveal the at least one signal; and

locating the at least one signal using a monitoring array comprising at least three monitoring units.

2. The method of claim 1 , wherein the knowledge map comprises an array of normal distributions, wherein each normal distribution corresponds to how often a power level at each frequency has been detected at a particular level.

3. The method of claim 1 , further comprising creating a profile of the RF environment based on the knowledge map, wherein the profile comprises a highest power level at each frequency during the learning period.

4. The method of claim 1 , further comprising automatically fine-tuning a threshold of a power level on a segmented basis while extracting at least one temporal feature from the knowledge map.

5. The method of claim 1 , further comprising periodically reevaluating the RF environment and updating the knowledge map.

6. The method of claim 1 , further comprising sending a notification and/or an alarm to an operator after detecting the at least one signal.

7. The method of claim 1 , further comprising displaying the knowledge map and/or detecting results in real time on a remote device.

8. The method of claim 1 , wherein the learning period is a predetermined period of time or a period of time required to reach a settled percent.

9. The method of claim 1 , wherein locating the at least one signal using a monitoring array comprising at least three monitoring units further comprises:

the at least three monitoring units scanning independently for the at least one signal;

at least one of the at least three monitoring units acquiring and measuring the at least one signal;

the at least one of the at least three monitoring units transmitting a formatted message to other units within the monitoring array; and

the at least one of the at least three monitoring units processing measurements of the at least one signal and determining a location of a signal emitting device from which the at least one signal is emitted;

wherein the formatted message comprises center frequency, bandwidth, modulation schema, average power, and phase lock loop time adjustment from the at least one of the at least three monitoring units.

10. The method of claim 1 , further comprising indexing the power level measurements for each frequency interval in a spectrum section in the learning period.

11. The method of claim 1 , further comprising determining exact locations of the at least three monitoring units and a timing of signal processing based on GPS information received by a GPS receiver in each of the at least three monitoring units.

12. A system for automatic signal detection in a radio-frequency (RF) environment, comprising:

at least one apparatus for detecting signals in the RF environment; and

a monitoring array comprising at least three monitoring units;

wherein the at least one apparatus is operable to sweep and learn the RF environment in a learning period based on statistical learning techniques, thereby creating learning data including power level measurements of the RF environment;

wherein the at least one apparatus is operable to form a knowledge map based on the power level measurements of the RF environment;

wherein the at least one apparatus is operable to scrub a real-time spectral sweep against the knowledge map;

wherein the at least one apparatus is operable to calculate a first derivative of the power level measurements and a second derivative of the power level measurements;

wherein the at least one apparatus is operable to select most prominent derivatives of the first derivative and the second derivative;

wherein the at least one apparatus is operable to perform a squaring function on the most prominent derivatives;

wherein the at least one apparatus is operable to identify at least one signal in the RF environment based on matched positive and negative gradients;

wherein the at least one apparatus is operable to average the real-time spectral sweep, remove areas identified by the matched positive and negative gradients, and connect points between removed areas to determine a baseline;

wherein the at least one apparatus is operable to subtract the baseline from the real-time spectral sweep to reveal the at least one signal; and

wherein the at least three monitoring units determine a location of a signal emitting device from which the at least one signal is emitted.

13. The system of claim 12 , wherein the knowledge map comprises an array of normal distributions, wherein each normal distribution corresponds to how often a power level at each frequency has been detected at a particular level.

14. The system of claim 12 , further comprising a remote device in network-based communication with the at least one apparatus, wherein the knowledge map and/or detecting results are displayed on a remote device in real time.

15. The system of claim 12 , wherein the learning period is a predetermined period of time or a period of time required to reach a settled percent.

16. The system of claim 12 , wherein the monitoring array is deployable and/or asymmetrical.

17. The system of claim 12 , wherein each of the at least three monitoring units comprise a GPS receiver for timing of signal processing and determining an exact location of the at least three monitoring units.

18. The system of claim 12 , wherein:

each of the at least three monitoring units comprises an antenna;

the at least three monitoring units are operable to scan independently for the at least one signal;

each of the at least three monitoring units is operable to measure the at least one signal and transmit a formatted message to other units within the monitoring array; and

each of the at least three monitoring units is operable to process measurements of the at least one signal and determine a location of a signal emitting device from which the at least one signal is emitted;

wherein the formatted message comprises center frequency, bandwidth, modulation schema, average power, and phase lock loop time adjustment from at least one of the at least three monitoring units.

19. The system of claim 12 , wherein the at least one apparatus is operable to index the power level measurements for each frequency interval in a spectrum section in the learning period.

20. The system of claim 12 , further comprising an external processor, wherein the external processor is operable to process the measurements of the at least one signal and determine the location of the signal emitting device from which the at least one signal is emitted.

Assignments (3)

Continuity (22)