A method for creating a virtual reception channel in a radar system includes an antenna possessing two physical reception channels (1.sub.r, 2.sub.r) spaced apart by a distance d in a direction x, two emission channels (1.sub.e, 2.sub.e) spaced apart by the same distance d in the same direction x and processing means, the method comprising: dynamically selecting two different waveforms, the waveforms being orthogonal to each other; generating a radar pulse of given central wavelength in each emission channel, each of the emission channels emitting one of the two different waveforms; acquiring with the reception channels echoes due to pulses emitted by the emission channels and reflected by at least one target; compressing the pulses by matched filtering of the echoes acquired by each physical reception channel, this involving correlating them with each of the waveforms generated in the emission channel; and repeating steps a) to c) while randomly changing one of the values of each of the phase codes associated with the generated waveforms until the level of the sidelobes of all the compressed pulses has stabilized; and radar system for implementing such a method.

An imaging method using a doppler radar wherein the pointing direction in transmission (d.sub.ei) is modified from recurrence to recurrence; each detection block of duration T comprises a periodic repetition of a number C of pointing cycles, each of these cycles comprising a number P of recurrences, the set of these P recurrences covering the D.sub.e pointing directions (d.sub.ei) of the set; the order of the pointings is modified in a pseudo-random manner from pointing cycle to pointing cycle during a same detection block so as to create an irregular time interval between two pointings in a same direction; at least one beam is formed in reception on each recurrence in a direction included in the transmission-focused angular domain in the pointing direction corresponding to the recurrence.

A computer-implemented method of navigating a vertical take-off and landing (“VTOL”) vehicle near a landing zone, may comprise receiving data related to a first radar signal reflected from at least one corner reflector; determining whether the received data is consistent with a predefined target landing zone; upon determining that the received data is consistent with the predefined target landing zone, determining a location of the VTOL vehicle relative to the predefined target landing zone, using a second radar signal reflected from at least one corner reflector; and determining whether the location of the VTOL vehicle is consistent with a predefined landing position.

Various systems and methodologies may be utilized to determine whether a particular shipment/item is eligible for delivery between a manual delivery vehicle and a final destination location via an autonomous delivery vehicle. To ensure autonomous deliveries are performed in a resource effective manner, shipments/items deemed eligible for autonomous delivery may be vetted by comparing the destination for the autonomous delivery shipment/item against one or more manual delivery destinations (serviced by the manual delivery vehicle operator), and ultimately identifying an optimal launch location for the autonomous delivery vehicle to leave the manual delivery vehicle to complete the autonomous delivery. If the autonomous delivery location does not satisfy applicable autonomous delivery criteria, the autonomous delivery shipment/item may be reclassified for manual delivery by the manual delivery vehicle operator.

Embodiments described herein may relate to an unmanned aerial vehicle (UAV) navigating to a target in order to provide medical support. An illustrative method involves a UAV (a) determining an approximate target location associated with a target, (b) using a first navigation process to navigate the UAV to the approximate target location, where the first navigation process generates flight-control signals based on the approximate target location, (c) making a determination that the UAV is located at the approximate target location, and (d) in response to the determination that the UAV is located at the approximate target location, using a second navigation process to navigate the UAV to the target, wherein the second navigation process generates flight-control signals based on real-time localization of the target.

Improvements in Global Navigation Satellite System (GNSS) spoofing detection of a vehicle are disclosed utilizing bearing and/or range measurements acquired independently from GNSS technology. Bearing and/or range measurements are determined from a GNSS-calculated position. Additionally, bearing and/or range measurements are acquired from an independent sensor, such as a Radio Detection and Ranging (radar) and a terrain database. The differences between the GNSS-based bearing and/or range and the bearing and/or range determined from the independent sensor, along with any applicable sources of error or uncertainty (including the post-hoc residuals from the GNSS-calculated position), are input into an analytical algorithm (e.g., RAIM) to determine whether GNSS spoofing is present with respect to the calculated GNSS position. If spoofing is detected, an alternative position determining system can be used in lieu of GNSS technology, and alerts can be sent notifying appropriate entities of the spoofing result.

An aircraft display system to present a real-time, three-dimensional depiction of a region around an aircraft, where this three-dimensional depiction is fixed to the aircraft's coordinate location and attitude. As the aircraft moves in attitude (e.g. roll, pitch, or yaw), in altitude (e.g., climbing and descending), and/or laterally, the three-dimensional depiction tilts and moves with the aircraft. The display may include a three-dimensional volumetric representation that may identify and prioritize hazards in the region around the aircraft. The aircraft display system may combine data from a plurality of sensors into a composite, real-time, three-dimensional synthetic vision display that determines a priority for each hazard.

Methods, apparatuses, and systems for predicting radio altimeter failures are provided. An example method may include determining a first plurality of altitude values associated with a first radio altimeter, determining a second plurality of altitude values associated with a second radio altimeter, calculating a first level feature based at least in part on the first plurality of altitude values and the second plurality of altitude values, and determining a radio altimeter failure indicator based at least in part on the first level feature.

Methods, apparatuses, and systems for predicting radio altimeter failures are provided. An example method may include determining a first plurality of altitude values associated with a first radio altimeter, determining a second plurality of altitude values associated with a second radio altimeter, calculating a first level feature based at least in part on the first plurality of altitude values and the second plurality of altitude values, and determining a radio altimeter failure indicator based at least in part on the first level feature.

Methods, devices, and systems are disclosed synchronizing clocks of FMCW radar units by transmitting a first signal of a first FMCW radar unit, a frequency of the first signal varying over a first frequency range around a first baseband frequency, receiving a second signal at the first FMCW radar unit, a frequency of the second signal varying over a second frequency range around a second baseband frequency, determining values of a plurality of parameters including a first timing offset of the first FMCW radar unit based on a digital difference signal between the first and second signals, receiving a second timing offset of a second FMCW radar unit, determining a clock offset based on the first and second timing offsets, and synchronizing a clock of the first FMCW radar unit with a clock of the second FMCW radar unit based on the clock offset.