Abstract: Systems, methods and apparatus are disclosed for automatic signal detection in an RF environment. An apparatus comprises at least one receiver and at least one processor coupled with at least one memory. The apparatus is at the edge of a communication network. The apparatus sweeps and learns the RF environment in a predetermined period based on statistical learning techniques, thereby creating learning data. The apparatus forms a knowledge map based on the learning data, scrubs a real-time spectral sweep against the knowledge map, and creates impressions on the RF environment based on a machine learning algorithm. The apparatus is operable to detect at least one signal in the RF environment.

Abstract: Systems, methods, and apparatus for geolocating a signal emitting device are disclosed. A monitoring array comprises at least four monitoring units. A distance ratio between the at least four monitoring units relative to a midpoint is determined. The at least four monitoring units are operable to scan independently for a signal of interest. The at least four monitoring units are operable to calculate times of arrival and angles of arrival for the signal of interest. Each of the at least four monitoring units is operable to measure the signal of interest and transmit a formatted message to other monitoring units within the monitoring array. Each of the at least four monitoring units is operable to determine a location of the signal emitting device from which the signal of interest is emitted based on calculations and measurements relating to the signal of interest.

Abstract: Systems, methods and apparatus for spectrum data management for a radio frequency (RF) environment are disclosed. An apparatus comprises at least one receiver, an automatic signal detection (ASD) module, and a learning and conflict detection engine. The apparatus is at the edge of a communication network. The at least one receiver processes RF energy received from the RF environment, thereby generating processed data. The ASD module is configured to extract meta data and detect anomaly based on the processed data. The learning and conflict detection engine is configured for conflict recognition and anomaly identification based on the processed data. The apparatus is operable to generate at least one report for the RF environment.

Abstract: Apparatus and methods for identifying a wireless signal-emitting device are disclosed. The apparatus is configured to sense and measure wireless communication signals from signal-emitting devices in a spectrum. The apparatus is operable to automatically detect a signal of interest from the wireless signal-emitting device and create a signal profile of the signal of interest; compare the signal profile with stored device signal profiles for identification of the wireless signal-emitting device; and calculate signal degradation data for the signal of interest based on information associated with the signal of interest in a static database including noise figure parameters of a wireless signal-emitting device outputting the signal of interest. The signal profile of the signal of interest, profile comparison result, and signal degradation data are stored in the apparatus.

Abstract: Systems, methods, and apparatus for detecting UAVs in an RF environment are disclosed. An apparatus is constructed and configured for network communication with at least one camera. The at least one camera captures images of the RF environment and transmits video data to the apparatus. The apparatus receives RF data and generates FFT data based on the RF data, identifies at least one signal based on a first derivative and a second derivative of the FFT data, measures a direction from which the at least one signal is transmitted, analyzes the video data. The apparatus then identifies at least one UAV to which the at least one signal is related based on the analyzed video data, the RF data, and the direction from which the at least one signal is transmitted, and controls the at least one camera based on the analyzed video data.

Abstract: Systems and methods for automated unmanned aerial vehicle recognition. A multiplicity of receivers captures RF data and transmits the RF data to at least one node device. The at least one node device comprises a signal processing engine, a detection engine, a classification engine, and a direction finding engine. The at least one node device is configured with an artificial intelligence algorithm. The detection engine and classification engine are trained to detect and classify signals from unmanned vehicles and their controllers based on processed data from the signal processing engine. The direction finding engine is operable to provide lines of bearing for detected unmanned vehicles.

Abstract: Systems, methods, and devices enable spectrum management by identifying, classifying, and cataloging signals of interest based on radio frequency measurements. In an embodiment, signals and the parameters of the signals may be identified and indications of available frequencies may be presented to a user. In another embodiment, the protocols of signals may also be identified. In a further embodiment, the modulation of signals, data types carried by the signals, and estimated signal origins may be identified.

Abstract: Systems, methods and apparatus are disclosed for automatic signal detection in an RF environment. An apparatus comprises at least one receiver and at least one processor coupled with at least one memory. The apparatus is at the edge of a communication network. The apparatus sweeps and learns the RF environment in a predetermined period based on statistical learning techniques, thereby creating learning data. The apparatus forms a knowledge map based on the learning data, scrubs a real-time spectral sweep against the knowledge map, and creates impressions on the RF environment based on a machine learning algorithm. The apparatus is operable to detect at least one signal in the RF environment.

Abstract: Systems, methods, and apparatus for geolocating a signal emitting device are disclosed. A monitoring array comprises at least four monitoring units. A distance ratio between the at least four monitoring units relative to a midpoint is determined. The at least four monitoring units are operable to scan independently for a signal of interest. The at least four monitoring units are operable to calculate times of arrival and angles of arrival for the signal of interest. Each of the at least four monitoring units is operable to measure the signal of interest and transmit a formatted message to other monitoring units within the monitoring array. Each of the at least four monitoring units is operable to determine a location of the signal emitting device from which the signal of interest is emitted based on calculations and measurements relating to the signal of interest.

Abstract: Systems, methods and apparatus for spectrum data management for a radio frequency (RF) environment are disclosed. An apparatus comprises at least one receiver, an automatic signal detection (ASD) module, and a learning and conflict detection engine. The apparatus is at the edge of a communication network. The at least one receiver processes RF energy received from the RF environment, thereby generating processed data. The ASD module is configured to extract meta data and detect anomaly based on the processed data. The learning and conflict detection engine is configured for conflict recognition and anomaly identification based on the processed data. The apparatus is operable to generate at least one report for the RF environment.

Abstract: Apparatus and methods for identifying a wireless signal-emitting device are disclosed. The apparatus is configured to sense and measure wireless communication signals from signal-emitting devices in a spectrum. The apparatus is operable to automatically detect a signal of interest from the wireless signal-emitting device and create a signal profile of the signal of interest; compare the signal profile with stored device signal profiles for identification of the wireless signal-emitting device; and calculate signal degradation data for the signal of interest based on information associated with the signal of interest in a static database including noise figure parameters of a wireless signal-emitting device outputting the signal of interest. The signal profile of the signal of interest, profile comparison result, and signal degradation data are stored in the apparatus.

Abstract: Systems, methods and apparatus for automatic alarm management in a radio-frequency (RF) environment are disclosed. An apparatus calculates a power distribution by frequency of the RF environment in real time or near real time, including a first derivative and a second derivative of FFT data of the RF environment. The apparatus then creates a baseline based on the power distribution by frequency of the RF environment in a period of time, identifies at least one alarm situation based on a multiplicity of alarm triggering conditions by comparing the power distribution in real time or near real time to the baseline of the RF environment, identifies at least one signal based on the first derivative and the second derivative of FFT data in the at least one alarm situation, and sends at least one alarm comprising details of the at least one signal identified in the at least one alarm situation.

Abstract: Systems, methods, and devices enable spectrum management by identifying, classifying, and cataloging signals of interest based on radio frequency measurements. In an embodiment, signals and the parameters of the signals may be identified and indications of available frequencies may be presented to a user. In another embodiment, the protocols of signals may also be identified. In a further embodiment, the modulation of signals, data types carried by the signals, and estimated signal origins may be identified.

Abstract: Systems, methods and apparatus are disclosed for automatic signal detection in an RF environment. An apparatus comprises at least one receiver and at least one processor coupled with at least one memory. The apparatus is at the edge of a communication network. The apparatus sweeps and learns the RF environment in a predetermined period based on statistical learning techniques, thereby creating learning data. The apparatus forms a knowledge map based on the learning data, scrubs a real-time spectral sweep against the knowledge map, and creates impressions on the RF environment based on a machine learning algorithm. The apparatus is operable to detect at least one signal in the RF environment.

Abstract: Systems, methods and apparatus for spectrum data management for a radio frequency (RF) environment are disclosed. An apparatus comprises at least one receiver, an automatic signal detection (ASD) module, and a learning and conflict detection engine. The apparatus is at the edge of a communication network. The at least one receiver processes RF energy received from the RF environment, thereby generating processed data. The ASD module is configured to extract meta data and detect anomaly based on the processed data. The learning and conflict detection engine is configured for conflict recognition and anomaly identification based on the processed data. The apparatus is operable to generate at least one report for the RF environment.

Abstract: Systems, methods, and apparatus for geolocating a signal emitting device are disclosed. A monitoring array comprises at least four monitoring units. A distance ratio between the at least four monitoring units relative to a midpoint is determined. The at least four monitoring units are operable to scan independently for a signal of interest. The at least four monitoring units are operable to calculate times of arrival and angles of arrival for the signal of interest. Each of the at least four monitoring units is operable to measure the signal of interest and transmit a formatted message to other monitoring units within the monitoring array. Each of the at least four monitoring units is operable to determine a location of the signal emitting device from which the signal of interest is emitted based on calculations and measurements relating to the signal of interest.

Abstract: Apparatus and methods for identifying a wireless signal-emitting device are disclosed. The apparatus is configured to sense and measure wireless communication signals from signal-emitting devices in a spectrum. The apparatus is operable to automatically detect a signal of interest from the wireless signal-emitting device and create a signal profile of the signal of interest; compare the signal profile with stored device signal profiles for identification of the wireless signal-emitting device; and calculate signal degradation data for the signal of interest based on information associated with the signal of interest in a static database including noise figure parameters of a wireless signal-emitting device outputting the signal of interest. The signal profile of the signal of interest, profile comparison result, and signal degradation data are stored in the apparatus.

Abstract: Systems and method for identifying a signal emitting device are disclosed in the present invention. A deployable large scale monitoring array comprises at least three monitoring units. Each of the at least three monitoring units comprises an antenna. The at least three monitoring units are operable to scan independently for a signal of interest. At least one of the at least three monitoring units is operable to measure the signal of interest and transmit a formatted message to other units within the array of antennas. None of the at least three monitoring units are full-time master or slave. Each of the at least three monitoring units is operable to process measurements of the signal of interest and determine a location of the signal emitting device from which the signal of interest is emitted.

Abstract: A method for identifying a missing neighbor in a wireless network includes receiving a report about two or more pilot signals measured by a mobile station; determining that one or more of the reported pilot signals is a missing neighbor not comprised in a current neighbor list of the mobile station; choosing one or more candidate sectors having a pilot signal with the same pilot identity as the missing neighbor; and selecting a most likely sector as the missing neighbor from the one or more candidate sectors, based on calculated distances between the mobile station and a source sector, between the mobile station and at least one of the one or more candidate sectors, and between the source sector and at least one of the one or more candidate sectors, so as to identify the missing neighbor in the wireless network.

Abstract: A method for identifying a missing neighbor in a wireless network includes receiving a report about two or more pilot signals measured by a mobile station; determining that one or more of the reported pilot signals is a missing neighbor not comprised in a current neighbor list of the mobile station; choosing one or more candidate sectors having a pilot signal with the same pilot identity as the missing neighbor; and selecting a most likely sector as the missing neighbor from the one or more candidate sectors, based on calculated distances between the mobile station and a source sector, between the mobile station and at least one of the one or more candidate sectors, and between the source sector and at least one of the one or more candidate sectors, so as to identify the missing neighbor in the wireless network.