The present disclosed subject matter relates to a method for measuring the distance of targets in the surroundings by way of a time-of-flight measurement of pulses reflected at said targets, in particular laser pulses, said method comprising: emitting a sequence of transmission pulses having varying pulse intervals, and receiving at least one receive pulse after each one of two different transmission pulses; for each receive pulse: generating a group of M candidate distances, each based on a different transmission pulse among M transmission pulses preceding the receive pulse, wherein each candidate distance is assigned to the corresponding transmission pulse on which it is based; for each candidate distance: determining a weighting value on the basis of at least the closest of the candidate distances assigned to such a transmission pulse which is adjacent to the transmission pulse to which the candidate distance being considered in this determining process is assigned; for each group: selecting the candidate distance with the highest weighting value as the distance measurement value of the receive pulse for which the group was generated.

The present disclosed subject matter relates to a method for measuring the distance of targets in the surroundings by way of a time-of-flight measurement of pulses reflected at said targets, in particular laser pulses, said method comprising: emitting a sequence of transmission pulses having varying pulse intervals, and receiving at least one receive pulse after each one of two different transmission pulses; for each receive pulse: generating a group of M candidate distances, each based on a different transmission pulse among M transmission pulses preceding the receive pulse, wherein each candidate distance is assigned to the corresponding transmission pulse on which it is based; for each candidate distance: determining a weighting value on the basis of at least the closest of the candidate distances assigned to such a transmission pulse which is adjacent to the transmission pulse to which the candidate distance being considered in this determining process is assigned; for each group: selecting the candidate distance with the highest weighting value as the distance measurement value of the receive pulse for which the group was generated.

Distribution fitting Constant False Alarm Rate (CFAR) detection is described. Noise data in cells or bins around a target cell are fit to a noise distribution model, such as a Rayleigh distribution model. With a suitable noise distribution curve from the distribution model, a CFAR threshold for that cell along the curve can be determined. A quantile function of the noise distribution model for a bin or cell provides the CFAR threshold to use for that bin or cell. Distribution fitting CFAR enables a more-accurate CFAR threshold to be set for each bin or cell and may use far fewer computing resources than Ordered-Statistics CFAR. A radar detector can better prevent false alarm detections across multiple different driving scenarios by adapting to different environments and dynamically changing the noise distribution curve used depending on best-fit analysis by a noise distribution model of noise characteristics of the neighboring bins or cells.

Distribution fitting Constant False Alarm Rate (CFAR) detection is described. Noise data in cells or bins around a target cell are fit to a noise distribution model, such as a Rayleigh distribution model. With a suitable noise distribution curve from the distribution model, a CFAR threshold for that cell along the curve can be determined. A quantile function of the noise distribution model for a bin or cell provides the CFAR threshold to use for that bin or cell. Distribution fitting CFAR enables a more-accurate CFAR threshold to be set for each bin or cell and may use far fewer computing resources than Ordered-Statistics CFAR. A radar detector can better prevent false alarm detections across multiple different driving scenarios by adapting to different environments and dynamically changing the noise distribution curve used depending on best-fit analysis by a noise distribution model of noise characteristics of the neighboring bins or cells.

Techniques are disclosed for determining the location of an object using RF sensing. More specifically, an object may be detected in a wireless data communication network using radar techniques in which one or more base stations act as a transmitter and a mobile device (e.g., a user equipment (UE)) acts as a receiver in a bistatic or multi-static radar configuration. By comparing the time a line-of-sight (LOS) signal is received by the mobile device with that of an echo signal from a reflection of an RF signal from the object, a position of the object can be determined. Depending on desired functionality, this position can be determined by the UE, or by a network entity.

Techniques are disclosed for determining the location of an object using RF sensing. More specifically, an object may be detected in a wireless data communication network using radar techniques in which one or more base stations act as a transmitter and a mobile device (e.g., a user equipment (UE)) acts as a receiver in a bistatic or multi-static radar configuration. By comparing the time a line-of-sight (LOS) signal is received by the mobile device with that of an echo signal from a reflection of an RF signal from the object, a position of the object can be determined. Depending on desired functionality, this position can be determined by the UE, or by a network entity.

According to a first aspect, a pulsed radar comprises a transmitter; wherein the pulsed radar is arranged to generate a string of binary values; wherein the transmitter comprises a pulse generator arranged to generate a pulse signal comprising a series of transmit pulses with polarities determined in accordance with the string of binary values; wherein a first substring comprises a first series of values; wherein a second substring comprises a second series of values; wherein the second substring is different from the first substring; and wherein each value in the second series of values is either the same as or different from the corresponding value in the first series of values according to a repeating pattern; and wherein the string of binary values comprises at least the first substring and the second substring concatenated together and each optionally being reversed before concatenation.

According to a first aspect, a pulsed radar comprises a transmitter; wherein the pulsed radar is arranged to generate a string of binary values; wherein the transmitter comprises a pulse generator arranged to generate a pulse signal comprising a series of transmit pulses with polarities determined in accordance with the string of binary values; wherein a first substring comprises a first series of values; wherein a second substring comprises a second series of values; wherein the second substring is different from the first substring; and wherein each value in the second series of values is either the same as or different from the corresponding value in the first series of values according to a repeating pattern; and wherein the string of binary values comprises at least the first substring and the second substring concatenated together and each optionally being reversed before concatenation.

The present disclosure relates to position, navigation and timing (PNT) methods, systems, and transmitters. A method comprises receiving radio-frequency (RF) signals from a plurality of virtual transmitters and determining PNT information of a target object based on information obtained from the RF signals. A system comprises a plurality of virtual transmitters and a receiver. The plurality of virtual transmitters is configured to transmit radio-frequency (RF) signals that include PNT information. The receiver is configured to determine PNT information of a target object based on the PNT information. A transmitter comprises a high-frequency (HF) carrier generator, a waveform generator, and an antenna system. The HF carrier generator generates an HF carrier signal. The waveform generator generates a waveform that includes PNT information. The antenna system transmits the HF carrier signal to generate a subject ionospheric duct. The antenna system is further configured to transmit the waveform through the ionospheric duct.

The present disclosure relates to position, navigation and timing (PNT) methods, systems, and transmitters. A method comprises receiving radio-frequency (RF) signals from a plurality of virtual transmitters and determining PNT information of a target object based on information obtained from the RF signals. A system comprises a plurality of virtual transmitters and a receiver. The plurality of virtual transmitters is configured to transmit radio-frequency (RF) signals that include PNT information. The receiver is configured to determine PNT information of a target object based on the PNT information. A transmitter comprises a high-frequency (HF) carrier generator, a waveform generator, and an antenna system. The HF carrier generator generates an HF carrier signal. The waveform generator generates a waveform that includes PNT information. The antenna system transmits the HF carrier signal to generate a subject ionospheric duct. The antenna system is further configured to transmit the waveform through the ionospheric duct.