Granted Patent B2

US 12,652,116 · App. 18/176,689 · Granted Jun 9, 2026

Inventors: Kok Meng Wong (Singapore, SG); Rajashekar Durai (Singapore, SG)

Assignee: Rohde & Schwarz GmbH & Co. KG

H04B17/345G05B13/027H04B17/27H04W24/06

Abstract

Claims (36)

1 . A system for radio frequency, RF, anomaly or interference detection in an environment, comprising:

an unmanned vehicle which is configured to move through the environment;

at least one RF receiver which is mounted to the unmanned vehicle and which is configured to record RF spectral data at different locations in the environment;

at least one RF machine learning unit, RFMLU, wherein the RFMLU is configured to analyze the RF spectral data in order to detect RF anomalies or interferences;

wherein, in case of detecting an RF anomaly or interference with the RFMLU, the RF receiver is configured to record a baseband signal of an RF environment at the location of the detected RF anomaly or interference, and

wherein the system is operable in a learning mode in which the RF receiver is configured to record spectral training data, and in which the RFMLU is trained based on said spectral training data using a supervised and/or an unsupervised learning technique.

2 . The system of claim 1 ,

wherein the RF receiver is configured to record the baseband signal in an I/Q data format.

3 . The system of claim 1 ,

wherein the RF receiver is configured to continuously or periodically record the RF spectral data.

4 . The system of claim 1 ,

wherein the unmanned vehicle is an unmanned ground vehicle or a drone.

5 . The system of claim 1 ,

wherein the unmanned vehicle is configured to receive location data indicating its current location in the environment.

6 . The system of claim 5 ,

wherein, in case of detecting the RF anomaly or interference in the RF spectral data, the unmanned vehicle is configured to record the location at which the RF spectral data with the RF anomaly or interference was recorded.

7 . The system of claim 6 ,

wherein the unmanned vehicle is further configured to forward the baseband data together with the recorded location to a database of the system.

8 . The system of claim 1 ,

wherein the unmanned vehicle also carries the RFMLU.

9 . The system of claim 1 ,

wherein the unmanned vehicle is configured to move through the environment along a preset, a learned or a random path.

10 . The system of claim 1 ,

wherein, in the learning mode, the unmanned vehicle is configured to move through the environment and thereby to generate or update a map of the environment.

11 . The system of claim 1 ,

wherein the system is operable in an operating mode in which the RF receiver is configured to record the RF spectral data, and in which the RFMLU is configured to detect the RF anomalies or interferences in the RF spectral data based on its previous training.

12 . A method for radio frequency, RF, anomaly or interference detection in an environment, comprising the steps of:

moving at least one RF receiver through the environment using an unmanned vehicle;

recording RF spectral data with the RF receiver at different locations in the environment;

analyzing the recorded RF spectral data using a machine learning technique in order to detect RF anomalies or interferences;

in case of detecting an RF anomaly or interference, recording a baseband signal of an RF environment at the location of the detected RF anomaly or interference; and

recording spectral training data with the RF receiver, and training at least one RF machine learning unit, RFMLU, based on said spectral training data using a supervised and/or an unsupervised learning technique.

13 . The method of claim 12 ,

wherein the baseband data is recorded in an I/Q data format.

14 . The method of claim 12 , wherein the method comprises the further step of:

receiving location data indicating a current location of the unmanned vehicle in the environment.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (35)