Method and system for object detection and avoidance for an autonomous vehicle

Abstract

A method and system for object detection and avoidance for an autonomous vehicle is provided. The system comprises a plurality of directional antennas, at least one multi-channel transceiver and a controller. The controller is programmed with computer-executable instructions for detecting, a plurality of radio echo signals from one or more objects, estimating maneuver performance limitations of the autonomous vehicle based on the radio echo signals, and generating at least one collision avoidance maneuver for the at least one autonomous vehicle based on the plurality of maneuver performance limitations and collision risk logic.

Description

METHOD AND SYSTEM FOR OBJECT DETECTION AND AVOIDANCE FOR AN AUTONOMOUS VEHICLEField

[0001] The present disclosure relates generally to radar systems using reflection of radio waves for anti-collision purposes. More particularly, the present disclosure relates to a method and system for object detection and avoidance with an autonomous vehicle.Background

[0002] The accelerated growth of Unmanned Aircraft Systems (UAS) and fully autonomous aircraft systems in recent years underscores the need for mechanisms to mitigate the risk of mid-air collisions, to thereby enable the safe operations of the aircraft beyond the visual line of sight. Such operations would require a high degree of automation at the platform and operational levels, since autonomous or semi- autonomous aircraft are often flown in non-segregated and uncontrolled airspaces. A crucial element of the desired automation is fully automatic detect-and-avoid capability available onboard the autonomous vehicle, which would allow the remote pilot to see, sense, or detect conflicting aircraft or obstacles, and take the appropriate action to remain well-clear or avert a collision.

[0003] Several prior art methods for object detection and avoidance have been proposed. For example, a DAAMSIM - Detect and Avoid Modeling and Simulation Framework to determine detect-and-avoid requirements for autonomous vehicles have been developed by the National Research Council of Canada (NRC) [1], and this tool can be used by the detect-and-avoid system developers and integrators for derivation of their sensor requirements. The framework is developed for collision avoidance between a UAS with manned intruder aircraft, however, the outcomes of the simulation could be easily used for any autonomous vehicles after insertingproper maneuvering characteristics of the vehicle. One of the modules of the framework, a metrics module, outputs the objective measures and metrics of a detect-and-avoid system performance for encounters of an autonomous vehicle with the specific maneuvering characteristics and a ‘typical’ intruder. The collision is considered to occur when the intruder penetrates a standard NMAC (near-mid-air collision) cylinder around the UAS (500 ft horizontally, + / -100 ft vertically). Note, that other collision volumes could be used in this framework, accounting for the subtleties of any autonomous vehicles (e.g., 50 ft radius could be considered for autonomous cars.)

[0004] Simulation results of such environments have revealed a highly non-linear range function across the problem space of a UAS and intruder airspeeds and collision-course geometry, suggesting that the performance of the sensing instrument and avoidance algorithm are not uniform across the desired operational field-of-regard. Head-on cases dominate the range requirement, while shorter ranges are required for high azimuth configurations, suggesting that it may be possible to optimize certain detect-and-avoid system parameters as a function of azimuth. Note that similar simulation could be conducted for any autonomous vehicles, while “plugging in” the vehicle maneuvering characteristics, and ‘typical’ intruder characteristics. Using same tools one can derive the sensor range requirements to ensure safe collision avoidance between any autonomous vehicles. Those requirements could be used to adjust the radar transmit power from various directions.

[0005] The prior art includes U.S. Patent No. 8,965,679, which describes systems and methods operable to maintain a prescribed self-separation distance between a UAS and an object. In their example system, consecutive intruder aircraft locations relative to corresponding locations of the UAS are determined, wherein the location determination is based on current velocities of the intruder aircraft and a UAS, and wherein the determination is based on current flight paths of the intruder aircraft andUAS aircraft. At least one evasive maneuver for a UAS aircraft is computed using a processing system based on the determined consecutive intruder aircraft locations relative to the corresponding locations of UAS aircraft. However, computing UAS maneuver in proposed systems and methods do not include possible limitations of maneuver area by other than intruder aircraft.

[0006] The prior art also includes European Patent No. EP2442133B1 , which proposes system and method for collision avoidance for UASs. The system comprises a flight control circuitry configured to control a flight path of the UAS, a plurality of radar sensors configured to scan for objects within a preselected range of the UAS and to store scan information indicative of the objects detected within the preselected range, and a processing circuitry coupled to the flight control circuitry and configured to receive the scan information from each of the plurality of radar sensors, while determining, using multiple hypothesis tracking, maneuver information comprising whether to change the flight path of the UAS based on the scan information, and send the maneuver information to the flight control circuitry, wherein each of the plurality of radar sensors is configured to operate as a phased array. In another aspect, the invention relates to a method for collision avoidance system for a UAS, where the method includes scanning for objects within a preselected range of the UAS using a plurality of phased array radar sensors, receiving scanned information from each of the plurality of phased array radar sensors, wherein the scanned information includes information indicative of objects detected within the preselected range of the UAS, determining, using multiple hypothesis tracking, maneuver information including whether to change a flight path of the UAV based on the scan information, and sending the maneuver information to a flight control circuitry of the UAS. However, radar sensors are configured to scan for objects within a preselected range and do not provide enough information about what is happening around objects in a rapidly changing situation, which is usual for a UAS.

[0007] Lastly, the prior art also includes the Detect and AvolD Alerting Logic for Unmanned Systems (DAIDALUS) as developed by National Aeronautics and Space Administration (NASA) [2], DAIDALUS is a collection of algorithms for detect and avoid concept that supports the integration of UAS into the National Airspace System (NAS). DAIDALUS algorithms are based on a mathematical definition of the wellclear boundary. The following algorithms are implemented in DAIDALUS. Detection Logic: Determine the current well-clear status between two aircraft and compute a time-interval of predicted well-clear violation, assuming non-maneuvering trajectories; Maneuver Guidance Logic: Compute range of maneuvers, called bands, for maintaining well-clear status; Alerting Logic: Determine a well-clear threat level, based on a given alerting schema. DAIDALUS algorithms have been formally specified and verified for functional correctness in PVS. The PVS formal development is part of the NASA PVS Library. Furthermore, implementations of DAIDALUS algorithms in Java and C++ are available under NASA's Open-Source Agreement.

[0008] However, DAIDALUS algorithms do not select the collision avoidance maneuver (require a human-in the loop), do not conduct risk assessment of the maneuvers and do not assess available maneuver space. DAIDALUS algorithms also assume simple cylindrical or spherical sensor range. However, the NRC simulation results in DAAMSIM revealed a highly non-linear range function across the problem space of a UAS and intruder airspeeds and collision-course geometry, suggesting that the performance of the sensing instrument and avoidance algorithm are not uniform across the desired operational field-of-regard. Head-on cases dominate the range requirement, while shorter ranges are required for high azimuth configurations, suggesting that it may be possible to optimize certain detect-and- avoid system parameters as a function of azimuth and make changes in corresponding algorithms.Summary of the Disclosure

[0009] According to an aspect, there is provided a method of detection and avoidance of at least one object for at least one autonomous vehicle, the method comprising: transmitting, via a plurality of directional antennas disposed about the at least one autonomous vehicle, a plurality of radiofrequency wave signals, detecting, via the plurality of directional antennas, the presence of the at least one object based on a plurality of radiofrequency echo signals associated with the at least one object, generating, based on the plurality of radiofrequency echo signals, a 3-dimensional map of a plurality of maneuver performance limitations of the at least one autonomous vehicle, and generating at least one collision avoidance maneuver for the at least one autonomous vehicle based on the 3-dimensional map of the plurality of maneuver performance limitations.

[0010] According to another aspect, there is provided an object detection and avoidance system for at least one autonomous vehicle, the system comprising: a plurality of directional antennas disposed about the at least one autonomous vehicle for transmitting and receiving radiofrequency wave signals, a multi-channel transceiver for pre-processing the radiofrequency wave signals received from the plurality of directional antennas, wherein each of the plurality of directional antennas is coupled to a channel of the multi-channel transceiver; each channel of the multichannel transceiver comprising automatic gain control circuitry for range control of each channel based on a magnitude of a radio echo signal, and a controller connected to the multi-channel transceiver for controlling a collision avoidance maneuver of the at least one autonomous vehicle, based on radio echo signals received by the plurality of directional antennas from the at least one object.Brief Description of the Drawings

[0011] Embodiments will now be described, by way of example only, with reference to the attached Figures, wherein:

[0012] Figure 1 shows a schematic diagram of the object detection and avoidance system according to an embodiment of the present disclosure;

[0013] Figure 2 shows a schematic diagram of a 3-dimensional map of maneuver performance limitations of the at least one autonomous vehicle, as a result of an available maneuver space estimation by the embodiment of the object detection and avoidance system of Figure 1 .

[0014] Figure 3 shows a schematic diagram of the plurality of directional antennas, multi-channel transceiver and controller of the embodiment of the object detection and avoidance system in Figure 1 ;

[0015] Figure 4 shows a schematic diagram of the embodiment of the object detection and avoidance system in Figure 1 ;

[0016] Figure 5 shows a flow chart schematic of the method for object detection and avoidance, according to an embodiment of the present disclosure;

[0017] Figure 6 shows a flow chart schematic of an additional embodiment of the method for object detection and avoidance of Figure 5;

[0018] Figure 7 shows a flow chart schematic of an another, additional embodiment of the method for object detection and avoidance of Figure 5;

[0019] Figure 8 shows a flow chart schematic of yet another, additional embodiment of the method for object detection and avoidance of Figure 5;

[0020] Figure 9A shows a side-view diagram of the plurality of directional antennas, where the plurality of directional antennas is arranged as a monopulse directional antenna array with overlapping antenna patterns;

[0021] Figure 9B shows a graphical illustration of an amplitude of a plurality of radiofrequency wave signals transmitted by the plurality of directional antenna of the system of Figure 1 , were each of the plurality of radiofrequency wave signals are phase shifted and overlapping with adjacent radiofrequency wave signals of the plurality of radiofrequency wave signals;

[0022] Figure 10 shows a schematic diagram of the plurality directional antennas for the object detection and avoidance system of Figure 1 , where the plurality of directional antennas is regularly, angularly spaced from one another in an overlap configuration distributed about the autonomous vehicle;

[0023] Figure 11 shows a schematic diagram of the plurality directional antennas for the object detection and avoidance system of Figure 1 , where the plurality of directional antennas is distributed in a swarm of aerial autonomous vehicles;

[0024] Figure 12A shows a top view of the plurality directional antennas for the object detection and avoidance system of Figure 1 , where the plurality of directional antennas is distributed around a ground autonomous vehicle (car) and the plurality of directional antennas are regularly, angularly spaced from one another in an overlap configuration distributed about the autonomous vehicle;

[0025] Figure 12B shows a side view of the plurality directional antennas for the object detection and avoidance system of Figure 1 , where the plurality of directional antennas is distributed around a ground autonomous vehicle (car);

[0026] Figure 13 shows an embodiment of one of the pluralities of directional antennas of Figure 1 , where the one of plurality of directional antennas includes an antenna shielding component;

[0027] Figure 14 shows a schematic diagram of an embodiment of the controller in the object detection and avoidance system of Figure 1 , where the controller includes first, second, and third control elements; and

[0028] Figure 15 shows a schematic of the DAIDALUS algorithm as it could be implemented on the system of Figure 1.Detailed Description

[0029] For simplicity and clarity of illustration, where considered appropriate, reference numerals may be repeated among the Figures to indicate corresponding or analogous elements. In addition, numerous specific details are set forth in orderto provide a thorough understanding of the embodiment or embodiments described herein. However, it will be understood by those of ordinary skill in the art that the embodiments described herein may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the embodiments described herein. It should be understood at the outset that, although exemplary embodiments are illustrated in the figures and described below, the principles of the present disclosure may be implemented using any number of techniques, whether currently known or not. The present disclosure should in no way be limited to the exemplary implementations and techniques illustrated in the drawings and described below.

[0030] Various terms used throughout the present description may be read and understood as follows, unless the context indicates otherwise: “or” as used throughout is inclusive, as though written “and / or”; singular articles and pronouns as used throughout include their plural forms, and vice versa; similarly, gendered pronouns include their counterpart pronouns so that pronouns should not be understood as limiting anything described herein to use, implementation, performance, etc. by a single gender; “exemplary” should be understood as “illustrative” or “exemplifying” and not necessarily as “preferred” over other embodiments. Further definitions for terms may be set out herein; these may apply to prior and subsequent instances of those terms, as will be understood from a reading of the present description. It will also be noted that the use of the term “a” or “an” will be understood to denote “at least one” in all instances unless explicitly stated otherwise or unless it would be understood to be obvious that it must mean “one”.

[0031] As used herein, the terms “comprises” and “comprising” are to be construed as being inclusive and open ended, and not exclusive. Specifically, when used in the specification and claims, the terms “comprises” and “comprising”, and variations thereof mean the specified features, steps or components are included.These terms are not to be interpreted to exclude the presence of other features, steps, or components.

[0032] As used herein, the terms “about” and “approximately” are meant to cover variations that may exist in the upper and lower limits of the ranges of values, such as variations in properties, parameters, and dimensions.

[0033] Modifications, additions, or omissions may be made to the systems, apparatuses, and methods described herein without departing from the scope of the disclosure. For example, the components of the systems and apparatuses may be integrated or separated. Moreover, the operations of the systems and apparatuses disclosed herein may be performed by more, fewer, or other components and the methods described may include more, fewer, or other steps. Additionally, steps may be performed in any suitable order. As used in this document, “each” refers to each member of a set or each member of a subset of a set.

[0034] The embodiments described herein are exemplary (e.g., in terms of materials, shapes, dimensions, and constructional details) and do not limit by the claims appended hereto and any amendments made thereto. Persons skilled in the art will appreciate that there are yet more alternative implementations and modifications possible, and that the following examples are only illustrations of one or more implementations. The scope of the disclosure, therefore, is only to be limited by the claims appended hereto and any amendments made thereto.

[0035] Referring to Figures 1 to 3, there is provided an embodiment of the object detection and avoidance system 100 for the one or more autonomous vehicles 210. There is provided an object detection and avoidance system 100 for one or more autonomous vehicles 210, the system 100 being configured for detecting at least one object 200 and controlling the one or more autonomous vehicles 210 to avoid the one or more objects 200, while accounting for maneuverability limitations 230 of the one or more autonomous vehicles 210 in avoiding the one or more objects 200.

[0036] In some embodiments, the object detection and avoidance system 100 is a radar detect-and-avoid system on the one or more autonomous vehicles 210 where the radar detect-and-avoid system provides intruder vehicle detection and collision avoidance for the one or more autonomous vehicles 210. The radar detect-and-avoid system can include automatically adjustable range for detecting objects (including intruders / threats) in maneuver limited settings, such as in urban or mountainous areas. The radar detect-and-avoid system can provide maneuver guidance as a result of an available maneuver space, where the available maneuver space is generated based on a 3-dimensional maneuver space of the one or more autonomous vehicles 210 that defines one or more external limits of motion of the one or more autonomous vehicles 210.

[0037] According to an embodiment of the present disclosure, the system 100 comprises a plurality of directional antennas 110 that are disposed about the one or more autonomous vehicles 210 for transmitting and receiving radiofrequency wave signals, and a multi-channel transceiver 120 for pre-processing the radiofrequency wave signals received from the plurality of directional antennas 110. Each of the plurality of directional antennas 110 is coupled to a channel of the multi-channel transceiver 120, where each channel of the multi-channel transceiver 120 comprises automatic gain control circuitry 310 for range control of each channel based on a magnitude of the radiofrequency echo signal received by the channel from one of the plurality of directional antenna 110. The system 100 also comprises a controller 130 that is connected to the multi-channel transceiver 120 for controlling a collision avoidance maneuver of the one or more autonomous vehicles 210 based on radiofrequency echo signals from the one object which are received by the plurality of directional antennas 110.

[0038] In an embodiment, the one or more autonomous vehicles 210 are a single autonomous vehicle such as an unmanned aerial system (UAS) or an autonomous ground vehicle (A VS).

[0039] In an alternate embodiment, the one or more autonomous vehicles 210 are a plurality of autonomous vehicles, such as a swarm of UASs.

[0040] In some embodiments, the one or more objects 200 includes one or more intruder objects (such as an intruder vehicle) and the method of object detection and avoidance is a method of intruder detection and avoidance which can simultaneously and rapidly detect one or more different kinds of intruder objects approaching from different directions, while again accounting for limits of the maneuver performance of the one or more autonomous vehicles 210.

[0041] In some embodiments where the one or more objects 200 includes one or more intruder vehicles, the one or more intruder vehicles can be any of a balloon, an airship, a manned aircraft or an unmanned aircraft.

[0042] As provided above, the object detection and avoidance system 100 includes the plurality of directional antennas 110. The plurality of directional antennas 110 function as non-scanning directional antennas, transmitting radiofrequency wave to one or more regions surrounding the one or more autonomous vehicles 210, while also receiving radiofrequency echo signals reflected from the one or more objects 200.

[0043] In some embodiments of the detection and avoidance system 100, each of the plurality of directional antennas 110 are configured as continuous observation antennas which provide monostatic scanning radar signals. The maximum range of each of the plurality of directional antennas 110 can be estimated based on the transmitting power of each of the directional antenna. The maximum range equation for a monostatic scanning radar is given by the following:[L0044

[0045] Where: R - radar-to-target distance (range); o - radar target cross section; A - wavelength; Pr - received-signal power being equal to the receiver minimum detectable signal Smin; Pt - transmitted-signal power (at antenna terminals); Gt, - transmitting antenna power gain; Gr - receiving antenna power gain; Ft - patternpropagation factor for transmitting-antenna-to-target path; Fr - pattern propagation factor for target-to-receiving-antenna path; where: le- integrator efficiency; M- number of transmitted / received pulses per period of integration.

[0046] For the embodiments where the plurality of directional antennas 110 are the continuous observation, monopulse directional antennas, pulses may be transmitted and reflected from the one or more objects 200 continuously. This means that the directional antennas 110 can transmit to and receive many radiofrequency wave signals / radiofrequency echo signals per second, for any target direction. By implementing a directional radar array that provides a continuous wave radar with continuous object observation and integration of the received radio echo signals, the effective range of the directional antennas 110 is increased. Simultaneous correlation and integration of thousands of radiofrequency echo signals per second from each of the plurality of directional antennas 110 allows not only for the detection of low- level signals (low profile targets) but aids in the recognition and classification of radiofrequency echo signals (targets) by using diversity signals, polarization modulation, and intelligent processing.

[0047] By providing the detection and avoidance system 100 as a non-scanning, monopulse system 100, the required transmitting power of the system 100 will also be substantially decreased compared to conventional scanning systems, while also providing for an increased radar range by integrating two-to-three orders of magnitude more radiofrequency echo signals within a given time period.

[0048] In an embodiment, the plurality of directional antennas 110 and multichannel transceiver 120 are structured such that one or more of the radiofrequency wave signals transmitted by the plurality of directional antennas 110, and the radiofrequency echo signals received by the plurality of directional antennas 110 include a doppler shifted, transmitted signal component and at least one near-field, diffracted frequency spectrum signal component. The doppler shifted, transmitted signal component provides for the tracking of moving objects within the scanningrange of the plurality of directional antenna, and the at least one near-field, diffracted frequency spectrum signal component provides for the detection of static targets within the scanning range of the plurality of directional antenna.

[0049] In an additional embodiment, the plurality of directional antennas 110 and multi-channel transceiver 120 are structured such that each of the radiofrequency echo signals received by the plurality of directional antennas 110 include the doppler shifted, transmitted signal component, a plurality of near-field, diffracted frequency spectrum signal components, and at least one regional obstacle signal component.

[0050] In some embodiments of the object detection and avoidance system 100 such as shown in Figures 3, the plurality of directional antennas 110 are a plurality of monopulse, fixed-beamwidth directional antennas and define a fixed-beamwidth directional antenna array. The radiofrequency wave signals transmitted by the plurality of directional antennas 110 are monopulse radiofrequency wave signals. The radiofrequency wave signals transmitted by each of the plurality of directional antennas 110 define an antenna pattern 220 of each of the plurality of directional antennas 110. The monopulse, fixed beamwidth arrangement of the plurality of directional antennas 110 distributed around the one or more autonomous vehicles 210 provides for fast, accurate, and simultaneous detection of both static and dynamic objects (such as the one or more objects 200) in a region surrounding the one or more autonomous vehicles 210. In particular, the overlap configuration of the plurality of directional antennas 110 provides particularly fast, accurate, and simultaneous detection of both static and dynamic objects in the region surrounding the one or more autonomous vehicles 210.

[0051] In an additional embodiment of the plurality of directional antenna, the radiofrequency wave signals transmitted by the plurality of directional antennas 110 are radiofrequency, circularly polarized, electromagnetic wave signals.

[0052] In some embodiments of the object detection and avoidance system 100 such as shown in Figures 3 and 4, where the one or more objects 200 includes oneor more intruder vehicles, the plurality of directional antennas 110 and the multichannel transceiver 120 are configured such that each of the plurality of radiofrequency wave signals is a multiple-frequency radiofrequency wave signal. The multiple-frequency radiofrequency wave signal includes at least one frequency with a wavelength that is equal to or greater than a maximum dimension of the one or more intruder vehicles.

[0053] According to an embodiment of the present disclosure, there is provided a method of detection and avoidance of one or more objects 200 for one or more autonomous vehicles 210, while accounting for maneuverability limitations 230 of the one or more autonomous vehicles 210 in avoiding the one or more objects 200.

[0054] In the methods of detection and avoidance provided below, any of the steps in the method may be executed by the controller 130 of the detection and avoidance system 100 or may be executed through another aspect of the detection and avoidance system 100, where the execution of this step on the other aspect of the detection and avoidance system 100 is controlled by the controller 130. Said another way, the controller 130 of the detection and avoidance system 100 is programmed with computer-executable instructions for executing any of the steps of the method of detection and avoidance, or for controlling the directional antenna or multi-channel transceiver 120 to execute one or more of the steps of the method of detection and avoidance.

[0055] Referring to Figure 5, an embodiment of the method of detection and avoidance of one or more objects 200 for the one or more autonomous vehicles 210 are provided. The method of detection and avoidance is executable by the object detection and avoidance system 100 and comprises a first step S110 of transmitting, via the plurality of directional antennas 110 disposed about the one or more autonomous vehicles 210, a plurality of radiofrequency wave signals, and a second step S120 of detecting, via the plurality of directional antennas 110, the presence of the one or more objects 200 based on a plurality of radiofrequency echo signalsassociated with the one or more objects 200. The method of detection and avoidance also comprises a third step S130 of generating, based on the plurality of radiofrequency echo signals, a 3-dimensional map of a plurality of maneuver performance limitations 230 of the one or more autonomous vehicles 210, and a fourth step S140 of generating at least one collision avoidance maneuver for the one or more autonomous vehicles 210 based on the 3-dimensional map of the plurality of maneuver performance limitations.

[0056] As provided above, the object detection and avoidance system 100 can include circuitry or components for pre-processing the plurality of radiofrequency echo signals received by plurality of directional antennas 110. In an embodiment of the method of object detection and avoidance, the step S120 of detecting, via the plurality of directional antennas 110, the one or more objects 200 based on a plurality of radiofrequency echo signals associated with the one or more objects 200 includes a first sub-step S200 of receiving the plurality radio frequency echo signals from the one or more objects 200 via the plurality of directional antenna, and a second substep S210 of adjusting a gain value of each of the plurality of radiofrequency echo signals based on at least one predetermined threshold value. In this embodiment, the gain value of each of the plurality of radiofrequency echo signals is adjusted independently from the gain values of the other of the plurality of radiofrequency echo signals. The step S120 of detecting the one or more objects 200 also includes the sub-step S220 of digitizing each of the plurality of radiofrequency echo signals, and the sub-step S230 of synchronizing each of the plurality of radiofrequency echo signals via at least one processor element of the one or more autonomous vehicles 210.

[0057] In an additional embodiment of the sub-step S210, the at least one predetermined threshold value includes an upper threshold of a magnitude of the radiofrequency echo signals and a lower threshold of the magnitude of the radiofrequency echo signals.

[0058] In an additional embodiment of the method of object detection and avoidance such as shown in Figure 6, the step S120 of detecting, via the plurality of directional antennas 110, the one or more objects 200 based on a plurality of radiofrequency echo signals associated with the one or more objects 200 further includes a sub-step processing each of the plurality of radiofrequency echo signals via at least one Fast Fourier Transform step.

[0059] In another, additional embodiment of the method of object detection and avoidance, the sub-step 220 of digitizing each of the plurality of radiofrequency echo signals is executed directly within the plurality of directional antennas 110.

[0060] As provided above, the object detection and avoidance system 100 includes a controller 130 for estimating various maneuver performance limitations 230 of the 3-dimensional map for the one or more autonomous vehicles 210. In an embodiment of the method of object detection and avoidance such as shown in Figure 7, the step S130 of generating the 3-dimensional map of the plurality of maneuver performance limitations 230 further includes a first sub-step S310 of estimating a maneuver space of the one or more autonomous vehicles 210 based on the received plurality of radiofrequency echo signals. In this embodiment, the maneuver space defines one or more external limits of at least one dimension of movement of the one or more autonomous vehicles 210.

[0061] In an additional embodiment, at least one of the step S130 of generating the 3-dimensional map of the plurality of maneuver performance limitations 230 and the step first sub-step S310 of estimating a maneuver space of the one or more autonomous vehicles 210 based on the received plurality of radiofrequency echo signals includes a filtering step to filter noise is applied for generating the 3- dimensional map of the plurality of maneuver performance limitations 230 and / or the maneuver space of the one or more autonomous vehicles 210. The filtering step may comprise a Kalman filter, an Unscented Kalman filter or Particle filter.

[0062] The step S130 of generating the 3-dimensional map of the plurality of maneuver performance limitations 230 also includes a second sub-step S320 of estimating a relative position and velocity of the one or more objects 200 based on the received plurality of radiofrequency echo signals.

[0063] In executing the second sub-step S320 of estimating the relative position and velocity of the one or more objects 200, there are various processes by which this step can be accomplished.

[0064] In a first embodiment, the relative position and velocity of the one or more objects 200 are estimated based off a monopulse method step. In this method step, the plurality of radiofrequency echo signals received from at least two of the plurality of directional antennas 110 are compared to one another via a phase-comparison, monopulse step. This phase-comparison, monopulse step involves calculating a ratio of the amplitude of received radiofrequency echo signals for each of the at least two of the plurality of directional antennas 110, where a distance and / or velocity of the one or more objects 200 can be determined based of the ratios of the amplitudes of the radiofrequency echo signals in subset of antenna of the plurality of directional antennas 110.

[0065] In a second, alternate embodiment, the relative position and velocity of the one or more objects 200 are estimated based off a non-linear estimation algorithm. In this embodiment, the step of estimating the relative position and velocity of the one or more intruder vehicles includes a first sub-step of determining a plurality of positions of the one or more objects 200 at a plurality of time points based on the plurality of radiofrequency echo signals, and a second sub-step of applying a linear estimation algorithm or a nonlinear estimation algorithm to the plurality of positions to generate a real-time prediction of the relative position and velocity of the one or more objects 200.

[0066] In some embodiments of the method where the relative position and velocity of the one or more objects 200 are estimated based off a linear or a non-linear estimation algorithm. In one example, the nonlinear estimation algorithm is a Kalman filter algorithm.

[0067] Referring to Figure 8, an additional embodiment of the method for object detection and avoidance is provided. In this embodiment of the method for object detection and avoidance, the method further includes a step S135 of calculating a collision risk of the one or more autonomous vehicles 210 and the at least object 200, where the step S140 of generating at least one collision avoidance maneuver for the at least one autonomous vehicle 210 is based on both the 3-dimensional map of the plurality of maneuver performance limitations, and the collision risk of the at least one autonomous vehicle 210 and the at least one object 200.

[0068] In some embodiments, the collision risk is calculated based on at least one potential collision avoidance maneuver that could be performed. For example, a higher collision risk is proportional to higher closing velocities between an intruder and the UAS 210, and the maneuver being in proximity of terrain and other static obstacles, conducting a more evasive and aggressive maneuver. As such the avoidance maneuver is conducted over the least risky space, for example, preferably not over obstacles, and not too close to the intruder aircraft.

[0069] As provided herein, the collision avoidance maneuver for the one or more autonomous vehicles 210 is for collision avoidance with the one or more objects 200. In some embodiments of the object detection and avoidance system 100, the collision avoidance maneuver for the one or more autonomous vehicles 210 is generated based at least on the maneuver space of the one or more autonomous vehicles 210, the relative position and velocity of the one or more objects 200, and one or more autonomous vehicles 210 maneuver limitation. In some alternate embodiments of the object detection and avoidance system 100, the at least one collision avoidance maneuver for the one or more autonomous vehicles 210 is generated based on the maneuver space of the one or more autonomous vehicles 210, the relative position and velocity of the one or more objects 200, the one or moreautonomous vehicles 210 maneuver limitation, and the calculated collision risk of the autonomous vehicle and the one or more objects 200.

[0070] In an embodiment of the detection and avoidance system 100 such as shown in Figures 9A and 10 to 12B, the plurality of directional antennas 110 are disposed at regular angular positions about a perimeter of the one or more autonomous vehicles 210 such that the antenna pattern 220 of each of the plurality of directional antennas 110 overlaps with an antenna pattern 220 or each adjacent antenna of the plurality of directional antennas 110.

[0071] In an additional embodiment, the plurality of directional antennas 110 of the fixed-beamwidth directional antenna array are oriented in an overlap configuration such that the antenna pattern 220 of the radiofrequency wave signals transmitted from each of the directional antennas partially overlaps with the antenna pattern 220 of the radiofrequency wave signals transmitted from one or more adjacent antennas of the plurality of directional antennas 110. By providing the fixed- beamwidth directional antenna array of the plurality of directional antennas in the overlap configuration, the detection and avoidance system 100 can provide substantially simultaneous detection of multiple objects 200 in a whole or semisphere pattern about the one or more autonomous vehicles 210 without necessitating any scanning or switching motion of the plurality of directional antennas 110. In this overlap configuration, the plurality of directional antennas 110 are positioned such that part of the radiofrequency wave signals that is transmitted from a given directional antenna is reflected from the one or more objects 200 and is received, as the radiofrequency echo signal, by both the given directional antenna and a subset of the plurality of directional antennas 110 which are adjacent to the given directional antenna.

[0072] Said another way, in some embodiments of the method as disclosed herein, the step S110 of transmitting the plurality of radiofrequency wave signals is executed such that an antenna pattern of the plurality of radiofrequency wave signalsis oriented in a whole or semi-spherical pattern about the at least one autonomous vehicle 210, where the plurality of directional antennas 110 remain in fixed positions during the step of transmitting the plurality of radiofrequency wave signals. In this way, the plurality of directional antennas 110 provide substantially simultaneous scanning and detection of multiple object 200 in the region around the at least one autonomous vehicle without relying on any scanning or switching motion of the plurality of directional antennas 110.

[0073] In another, additional embodiment, the controller 130 of the object detection and avoidance system 100 can be programmed for determining a ratio of a radiofrequency echo signal that is received in a subset of the plurality of directional antenna 110 when the plurality of directional antennas 110 are in the overall configuration. In this embodiment, the ratio of the radiofrequency echo signal received by the subset can be determined based on one of the subset of the plurality of directional antennas 110 having transmitted a radiofrequency wave signal. The ratio of the radiofrequency echo signal in the subset of the plurality of directional antennas 110 represent the radar response in the subset of the plurality of directional antennas 110. The ratio of the subset of the plurality of directional antennas 110 can then be used to estimate an angle of arrival and / or range information of the one or more objects 200.

[0074] In some embodiments of the plurality of directional antennas 110, the plurality of directional antennas 110 are evenly distributed around the perimeter of the one or more autonomous vehicles 210 for transmitting radiofrequency waves omnidirectionally, and each of the plurality of directional antennas 110 are connected to a separate channel of the multi-channel transceiver 120.

[0075] In some alternate embodiments of the plurality of directional antennas 110, the plurality of directional antennas 110 are irregularly distributed around the perimeter of the one or more autonomous vehicles 210 for transmitting radiofrequency waves omnidirectionally, where the plurality of directional antennas110 are clustered arounds specific regions of interest of the one or more autonomous vehicles 210, such as a front or rear end of the vehicle. Again, each of the plurality of directional antennas 110 are connected to a separate channel of the multi-channel transceiver 120.

[0076] In some embodiments, the fixed-beamwidth directional antenna array is structured as a monopulse directional antenna array that transmits and receives continuous radiofrequency wave signals. In an alternate embodiment, the fixed- beamwidth directional antenna array is structured as a monopulse directional antenna array that transmits and receives pulsed radiofrequency wave signals.

[0077] In an embodiment of the one or more autonomous vehicles 210 such as shown in Figure 10, the one or more autonomous vehicles 210 are an aerial autonomous vehicle 810. In the specific embodiment provided in Figure 10, the plurality of directional antennas 110 are a plurality of angularly shifted directional antennas that are distributed evenly around the aerial autonomous vehicle 810. The even overlap antenna patterns 220 extend outwards from the aerial autonomous vehicle 810, and the overlap antenna patterns 220 provide for fast, accurate, and simultaneous detection of multiple objects 200 in a whole or semi-sphere pattern about the aerial autonomous vehicle 810 without scanning or switching the plurality of directional antennas 110.

[0078] In an additional embodiment of the one or more autonomous vehicles 210 shown in Figure 11 , the one or more autonomous vehicles 210 are a swarm of a plurality of airborne autonomous vehicles 810. In the specific embodiment provided in Figure 11 , the plurality of directional antennas 110 are one or more angularly shifted directional antennas that is distributed about each of the plurality of airborne autonomous vehicles 810. Each vehicle of the plurality of airborne autonomous vehicles 810 includes one or more of the plurality of directional antennas 110, and the swarm of the plurality of airborne autonomous vehicles 810 is controlled suchthat the antenna patterns 220 from the plurality of airborne autonomous vehicles 810 form overlapping antenna patterns 220.

[0079] In an embodiment of the one or more autonomous vehicles 210 shown in Figure 12A and 12B, the one or more autonomous vehicles 210 is a single ground autonomous vehicle 910. In the specific embodiment provided in Figures 9A and 9B, the plurality of directional antennas 110 are a plurality of angularly shifted directional antennas that are distributed evenly around the ground autonomous vehicle 910. The even overlap antenna patterns 220 extend outwards, upwards, and downwards from the ground autonomous vehicle 910.

[0080] In some embodiments of the detection and avoidance system 100 such as shown in Figure 13, each of the plurality of directional antennas 110 includes an antenna shielding component 1400 for at least partially separating the radiofrequency wave signals transmitted by each of the plurality of directional antennas 110 from one another. Each antenna shielding component 1400 of each of the plurality of directional antennas 110 consists of shielding composite material means for separation of antenna patterns 220 from the plurality of directional antennas 110 in space.

[0081] In an additional embodiment, the antenna shielding component 1400 of each of the plurality of directional antennas 110 is composed of a composite material that includes at least one layer of magnetic material, at least one layer of nonmagnetic material, and at least one layer of surface current absorbing material.

[0082] As provided above, the object detection and avoidance system 100 includes the multi-channel transceiver 120. The multi-channel transceiver 120 includes a plurality of separate channels that are each connected to a separate one of the plurality of directional antennas 110.

[0083] In an embodiment, each channel of the multi-channel transceiver 120 includes the automatic gain control circuitry 310 for separate range control in each direction of the plurality of directional antennas 110. The gain of the radiofrequencyecho signal in each channel of the multi-channel transceiver 120 is controlled based on the magnitude of the radiofrequency wave signal such that the gain of the radiofrequency echo signal received by each of the plurality of directional antennas 110 is dependent on magnitude of the received radar echo response in the direction towards which each of the plurality of directional antennas 110 is oriented.

[0084] In an additional embodiment, the multi-channel transceiver 120 is structured to provide high-power protection within each channel of the multi-channel receiver, and to provide a means for automatically switching off channel(s) of the multi-channel transceiver 120 if power the power in the channel(s) is above a specific power threshold. Each channel of the multi-channel transceiver 120 is connected to one or more limiter elements 336 for limiting a power of the radiofrequency echo signal received by the one of the plurality of directional antenna, and a high-power protection element 338 for switching off the channel of the multi-channel transceiver 120 if the power of the radiofrequency echo signal received by the one of the plurality of directional antennas 110 is above a predetermined power threshold.

[0085] In another embodiment of the multi-channel transceiver 120, each channel of the multi-channel transceiver 120 further includes one or more converter elements for digitizing the received radiofrequency echo signals.

[0086] In the specific embodiment of the multi-channel transceiver 120 shown in Figure 3, each directional antenna of the plurality of directional antennas 110 is coupled with a separate channel of multi-channel transceiver 120. The one or more converter elements includes software defined radio circuitry 330 that includes a frontend circuit and an analog-to-digital converter 332 connected by a digital interface 340 to the controller 130. The controller 130 can include a digital signal processor element 380, where the software defined radio circuitry 330 can be connected to the digital signal processor element 380 in the controller 130, via the digital interface 340.

[0087] In the additional embodiment shown in Figure 3, the multi-channel transceiver 120 includes synchronization circuitry 342 that is connected to thecontroller 130 and to each channel of the multi-channel transceiver 120 for synchronizing the radiofrequency echo signals received through each channel of multi-channel transceiver 120, via the plurality of directional antennas 110.

[0088] In the specific embodiment provided in Figure 3, the synchronization circuitry 342 is connected to each of the multi-channel transceiver 120 and controller 130 (via the digital interface 340) for synchronization and simultaneous processing of the radiofrequency echo signals in both the time and frequency domain.

[0089] In the embodiments where the radiofrequency wave signals are radiofrequency, circularly polarized, electromagnetic wave signals, the circular polarization of the radiofrequency wave signals (as opposed to simple vertical or horizontal polarization) facilitates the “catching” of all the radiofrequency echo signals during the digitization and synchronization of the plurality of radiofrequency echo signals received by the plurality of directional antennas 110.

[0090] As provided above, the object detection and avoidance system 100 also includes the controller 130. The controller 130 is provided in the object detection and avoidance system 100 for controlling a collision avoidance maneuver of the one or more autonomous vehicles 210 based on radiofrequency echo signals from the one object received by the plurality of directional antennas 110. The controller 130 is connected to the multi-channel transceiver 120 for processing the radiofrequency echo signals from the plurality of directional antennas 110 for extracting observation data from the radiofrequency echo signals. The observation data can be applied for generating the 3-dimensional maneuver space of the one or more autonomous vehicles 210 that defines one or more external limits of maneuverability based on information about the range of each channel of the multi-channel transceiver 120, as regulated by the automatic gain control circuitry 310 in each channel.

[0091] The controller 130 of the object detection and avoidance system 100 can include several physical and logical components, including a central processing unit (“CPU”), random access memory (“RAM”), a network interface, non-volatile storage,and a local bus enabling the CPU to communicate with the other components. RAM provides relatively responsive volatile storage to the CPU. The network interface permits communication with other systems. Non-volatile storage stores the operating system and programs, including computer-executable instructions for implementing the method for object detection and avoidance as described herein and the data associated with the execution of the method for object detection and avoidance. During operation of the controller 130, the programs and the data may be retrieved from the non-volatile storage and placed in RAM to facilitate execution. Computerexecutable instructions for implementing the method for object detection and avoidance on a computer system could be provided separately from the computer system, for example, on a computer-readable medium (such as, for example, an optical disk, a hard disk, a USB drive or a media card) or by making them available for downloading over a communications network, such as the Internet.

[0092] While the controller 130 is shown as a single physical computer system 100, it will be appreciated that the controller 130 can include two or more physical computers in communication with each other. Accordingly, while the embodiment shows the various components of the controller 130 residing on the same physical computer, those skilled in the art will appreciate that the components can reside on separate physical computers.

[0093] As provided above, some embodiments of the controller 130 includes the digital signal processor element 380. The digital signal processor element 380 in the controller 130 is structured to include particularities of FFT (Fast Fourier Transform) processing for determining the position and velocity of the one or more objects 200 based on the radiofrequency echo signals received from the plurality of directional antennas 110 and pre-processed via the multi-channel transceiver 120.

[0094] In an additional embodiment such as shown in Figure 1 , the controller 130 is connected to a control interface 140 of the one or more autonomous vehicles 210. In the embodiments where the controller 130 is connected to the control interface140 of the one or more autonomous vehicles 210, the controller 130 can be programmed with computer-executable instructions for, in a first step, generating at least one control signal based on the at least one collision avoidance maneuver for the one or more autonomous vehicles 210, and in a second step, relaying the at least one control signal to the control interface 140 of the one or more autonomous vehicles 210 for altering a travel path of the one or more autonomous vehicles 210.

[0095] In an alternate embodiment of the object detection and avoidance system 100, the controller 130 is connected to a remote control element of the one or more autonomous vehicles 210, where the remote control element is communicatively connected to a ground station. The ground station can be structured such that a pilot can view or control some aspects of the motion of the of the one or more autonomous vehicles 210 based on information received from the one or more autonomous vehicles 210.

[0096] In an additional embodiment such as shown in Figure 11, when the one or more autonomous vehicles 210 are the swarm of aerial autonomous vehicles 810, each vehicle 810 of the swarm includes a remote control element, and the remote control element of each of the aerial autonomous vehicles 810 is communicatively connected to a remote control element of a swarm leading autonomous vehicle 810a of the swarm of aerial autonomous vehicles 810, which in turn is connected to is communicatively connected to the ground station.

[0097] In some embodiments of the controller 130, the controller 130 includes a first control element 350. The first control element 350 includes at least one processor 354 and memory 352 with computer-readable instructions stored thereon. The computer-readable instructions are executable by the at least one processor 354 for generating, based on the plurality of radiofrequency echo signals, the 3- dimensional map of the plurality of maneuver performance limitations 230 of the one or more autonomous vehicles 210.

[0098] In an additional embodiment, the step of generating the 3-dimensional map of the plurality of maneuver performance limitations 230 of the one or more autonomous vehicles 210 further includes defining a 3-dimensional maneuver space of the one or more autonomous vehicles 210. The 3-dimensional maneuver space of the one or more autonomous vehicles 210 defines one or more external limits of at least one direction of movement of the one or more autonomous vehicles 210.

[0099] In some embodiment of the controller 130, the controller 130 also includes a second control element 360. The second control element 360 includes at least one processor 364 and memory 362 with computer-readable instructions stored thereon. The computer-readable instructions are executable by the at least one processor 364 for detecting, via the plurality of directional antennas 110, one or more objects 200 based on a plurality of radiofrequency echo signals from the one or more objects 200. The plurality of radiofrequency echo signals which reflect off the one or more objects 200, and which are received by the plurality of directional antenna, will indicate the presence of the one or more objects 200.

[0100] In an additional embodiment, the memory 362 of the second control element 360 is further programmed with computer-readable instructions that are executable for estimating a relative position and velocity of one or more objects 200 based on the received radiofrequency echo signals. The relative position and velocity of the one or more objects 200 can be estimated by applying various non-linear estimation algorithms to the received radiofrequency echo signals.

[0101] In an additional embodiment, the second control element 360 includes a Kalman filter component that is applied in estimating the position and velocity of the one or more objects 200. In this embodiment, the memory 362 of the second control element 360 is programmed with computer-readable instructions for determining a plurality of positions of the one or more objects 200 at a plurality of time points, based on the plurality of radiofrequency echo signals. The Kalman filter component of the second control element 360 processes the plurality of positions of the one or moreobjects 200 and the plurality of time points via a Kalman filter algorithm for generating a real-time prediction of the relative position and velocity of the one or more objects 200.

[0102] In some embodiments of object detection and avoidance system 100, the controller 130 includes a third control element 370 that utilizes maneuver limitation logic and risk assessment logic for selecting a collision avoidance maneuver of the one or more autonomous vehicles 210 based on the available, generated 3- dimensional maneuver space of the one or more autonomous vehicles 210, as well as additional risk assessment logic that is programmed into the third control element 370.

[0103] In an embodiment such as shown in Figure 14, the third control element 370 includes one or more processors 374 and memory 372 with computer-readable instructions stored thereon, vehicle maneuver limitation logic data 570 that defines a maximum degree of maneuverability of the one or more autonomous vehicles 210 in at least one dimensions of motion, and maneuver guidance logic data 572 that defines a likelihood of collision between the one or more autonomous vehicles 210 and the one or more objects 200 based on the relative distance between the one or more autonomous vehicles 210 and the one or more objects 200.

[0104] In another additional embodiment, the third control element 370 also includes a risk assessment logic 574 that is structured to provide risk assessment logic and, in some embodiments, consists of fuzzy logic, ruled-based system, or a cost function means. In this embodiment, the controlling of the collision avoidance maneuver of the one or more autonomous vehicles 210 is based on the generated 3-dimensional maneuver space, the maneuver limitation logic data 570, the maneuver guidance logic data 572, and the risk assessment logic provided by the risk assessment logic 574. As provided above, the 3-dimensional maneuver space defines one or more external limits, performance limits and risk assessment.

[0105] In an embodiment, the controlling of a collision avoidance maneuver of the one or more autonomous vehicles 210 includes a step of generating the collision avoidance maneuver of the one or more autonomous vehicles 210.

[0106] In an additional embodiment such as shown in Figures 14, the third control element 370 is connected to each of the first and second control elements 350, 360 within the controller 130. The controller 130 is programmed with computer executable instructions for generating at least one collision avoidance maneuver for the one or more autonomous vehicles 210 based on the 3-dimensional map of the plurality of maneuver performance limitations 230, the vehicle maneuver limitation logic data, collision risk logic data, and the relative position and velocity of the one or more objects 210.

[0107] In the specific embodiment provided in Figures 3 and 14, the controller 130 includes the digital signal processing element 380 with Kalman filters, and first, second and third control elements 350, 360, 370, all of which are connected to the multi-channel transceiver 120 via connections to the digital interface 340.

[0108] While the above objection detection and avoidance system has been described with specificity to a plurality of directional antennas connected to a multichannel transceiver 120 and the controller 130, alternate embodiments of the system can include multiple arrays of the plurality of directional antenna 110, and multiple modules that each contains a multi-channel transceiver 120.

[0109] In the specific embodiment provided in Figure 4, the object detection and avoidance system 100 includes multiple arrays of directional antennas 110 (only one is shown), and a plurality of transceiver modules 400, where each of the plurality of transceiver modules 400 is connected to one of the multiple arrays of directional antennas 110, and each of the plurality of transceiver modules 400 is connected to the controller 130 via the digital interface 340. As with the above-described plurality of directional antennas 110 and multi-channel transceiver 120, each of the plurality of directional antennas 110 in each transceiver module 400 is connected to one ofthe channels of the multi-channel transceiver 120 of the given transceiver module 400. Each transceiver module 400 consists of a plurality of receiving directional antennas 110a with overlap angular shifted antenna patterns 220, and as minimum one transmitting directional antenna 110b. Each directional antenna 110a, 110b is coupled with a separate channel of multi-channel transceiver 120, and includes the software defined radios circuitry 330 in each channel. Each software defined radios circuitry 330 consists of the front-end circuit 332 connected with directional antenna 110a, 110b and the analog to digital converter (ADC) 334 connected to controller 130 by the digital interface 340. Each transceiver module 400 also consists of transmitting channel with power amplifier 422, Phase Lock Loop (PLL) 424 and Clock Card (CLK) 426 connected to digital interface 340.

[0110] Figure 4 demonstrate a schematic of an embodiment of the controller 130 connected to the multi-channel transceiver 120. The controller 130 includes a plurality of control elements and is programmed for executing at least some of the steps of the method for object detection and avoidance as provided herein for controlling the collision avoidance maneuver of the one or more autonomous vehicles 210. The control of the collision avoidance maneuver can, is some embodiments, be based on the generated 3-dimensional maneuver space, the maneuver limitation logic data 570, the maneuver guidance logic 572 and the risk assessment logic 574 provided by the controller 130.

[0111] In some embodiments of the controller 130, the controller 130 is programmed for controlling the one or more autonomous vehicles 210 at least in part based on third-party algorithms and / or software for detecting and avoiding objects. The third-party algorithms / software supports the integration of detection and avoid logic within the one or more autonomous vehicles and can be programmed into the controller 130. The third-party algorithms and / or software for detecting and avoiding objects can be, in some embodiments, based on Detect and AvolD Alerting Logic for Unmanned Systems (DAIDALUS), as developed by the NASA. An exemplaryschematic of the control logic that is programmed into the existing DAIDALUS software is shown in Figure 15.

[0112] The specific embodiments described above have been shown by way of example, and it should be understood that these embodiments may be susceptible to various modifications and alternative forms. It should be further understood that the above-described embodiments are intended to be examples of the present disclosure and alterations and modifications may be affected thereto, by those of skill in the art, without departing from the scope of the disclosure that is defined solely by the claims appended hereto.

[0113] References1. Iryna Borshchova, & Kris Ellis. (2023). DAAMSIM (1.0). Zenodo. https: / / doi.org / 10.5281 / zenodo.8180065 Repository: https: / / github.com / nrc- cnrc / daamsim / blob / main / README.md2. Repository: https: / / github.com / nasa / WellClear / blob / master / DAIDALUS / C%2B%2B / src / Daidal usExample.cpp

Claims

CLAIMS:

1. A method of detection and avoidance of at least one object for at least one autonomous vehicle, the method comprising: transmitting, via a plurality of directional antenna disposed about the at least one autonomous vehicle, a plurality of radiofrequency wave signals; detecting, via the plurality of directional antennas, the presence of the at least one object based on a plurality of radiofrequency echo signals associated with the at least one object; generating, based on the plurality of radiofrequency echo signals, a 3-dimensional map of a plurality of maneuver performance limitations of the at least one autonomous vehicle; calculating a collision risk of the at least one autonomous vehicle and the at least one object, and generating at least one collision avoidance maneuver for the at least one autonomous vehicle based on the 3-dimensional map of the plurality of maneuver performance limitations and the collision risk of the at least one autonomous vehicle and the at least one object.

2. The method according to claim 1 , wherein the step of generating the 3- dimensional map of the plurality of maneuver performance limitations further includes: estimating a maneuver space of the at least one autonomous vehicle based on the received plurality of radiofrequency echo signals, the maneuver space defining one or more external limits of at least one dimension of movement of the at least one autonomous vehicle; and estimating a relative position and velocity of the at least one object based on the received plurality of radiofrequency echo signals.

3. The method according to claim 1, wherein the step of generating the 3- dimensional map of the plurality of maneuver performance limitations further includes at least one Kalman filtering step that is applied for generating the 3- dimensional map of the plurality of maneuver performance limitations 230.

4. The method according to claim 2, wherein the collision avoidance maneuver for the at least one autonomous vehicle is for collision avoidance with the at least one object, and wherein the collision avoidance maneuver for the at least one autonomous vehicle is generated based at least on the maneuver space of the at least one autonomous vehicle, the relative position and velocity of the at least one object, and at least one autonomous vehicle maneuver limitation.

5. The method according to claim 1 , wherein the at least one object includes at least one intruder vehicle.

6. The method according to claim 1 , wherein the radiofrequency wave signals transmitted by each of the plurality of directional antennas defines a wave signal pattern of each of the plurality of directional antennas, and wherein the plurality of directional antennas are disposed at regular angular positions about a perimeter of the at least one autonomous vehicle such that the wave signal pattern of each of the plurality of directional antennas overlaps with a wave signal pattern of each adjacent antenna of the plurality of directional antennas.

7. The method according to claim 1 , wherein each of the plurality of directional antennas is connected to a separate channel of a multi-channel transceiver.

8. The method according to claim 1 , wherein the radiofrequency wave signals are monopulse, radiofrequency, circularly polarized electromagnetic signals.

9. The method according to claim 1 , wherein the method further includes: generating at least one control signal based on the at least one collision avoidance maneuver of the at least one autonomous vehicle; and relaying the at least one control signal to a control interface of the at least one autonomous vehicle for guiding the at least one autonomous vehicle to follow the at least one collision avoidance maneuver.

10. The method according to claim 2, wherein the step of detecting, via the plurality of directional antennas, the at least one object based on a plurality of radiofrequency echo signals associated with the at least one object includes: receiving the plurality radio frequency echo signals from the at least one object via the plurality of directional antenna; adjusting a gain value of each of the plurality of radiofrequency echo signals based on at least one predetermined threshold value, wherein the gain value of each of the plurality of radiofrequency echo signals is adjusted independently from the gain values of the other of the plurality of radiofrequency echo signals; digitizing each of the plurality of radiofrequency echo signals; and synchronizing each of the plurality of radiofrequency echo signals via at least one processor element of the at least one autonomous vehicle.11 . The method according to claim 10, wherein the step of receiving the plurality of radiofrequency echo signals via the plurality of directional antenna further includes processing each of the plurality of radiofrequency echo signals via at least one Fast Fourier Transform step.

12. The method according to claim 10, wherein the step of digitizing each of the plurality of radiofrequency echo signals is executed within the plurality of directional antennas.

13. The method according to claim 10, wherein the at least one predetermined threshold value includes an upper threshold of a magnitude of the radiofrequency echo signals and a lower threshold of the magnitude of the radiofrequency echo signals.

14. The method according to claim 1 , wherein each of the plurality of radiofrequency echo signals received by the plurality of directional antennas includes: a doppler shifted, transmitted signal component; and at least one near-field, diffracted frequency spectrum signal component.

15. The method according to claim 2, wherein the step of estimating a relative position and velocity of the at least one object includes comparing the plurality of radiofrequency echo signals received from the plurality of directional antennas via a phase-comparison, monopulse step.

16. The method according to claim 2, wherein the step of estimating a relative position and velocity of the at least one object includes: determining a plurality of relative positions of the at least one object at a plurality of time points based on the plurality of radiofrequency echo signals; and applying at least one of a linear and a nonlinear estimation algorithm to the plurality of positions of the at least one object to generate a real-time prediction of the relative position and velocity of the at least one object.

17. The method according to claim 16, wherein the nonlinear estimation algorithm is a Kalman filter algorithm.

18. The method according to claim 5, wherein each of the plurality of radiofrequency wave signals is a multiple-frequency radio wave signal having at least one frequency with a wavelength that is equal to or greater than a maximum dimension of the at least one intruder vehicle.

19. The method according to claim 5, wherein the method further includes calculating a collision risk of the at least one autonomous vehicle and the at least one intruder vehicle, the collision risk defining a likelihood of collision between the at least one autonomous vehicle and the at least one intruder vehicle based on an estimated distance between the at least one autonomous vehicle and the at least one intruder vehicle.

20. The method according to claim 10, wherein the step of generating at least one collision avoidance maneuver for the at least one autonomous vehicle is for collision avoidance with the at least one object, and wherein the at least one collision avoidance maneuver for the at least one autonomous vehicle is generated based on the maneuver space of the at least one autonomous vehicle, the relative position and velocity of the at least one object, and the at least one autonomous vehicle maneuver limitation.

21. The method according to claim 10, wherein the step of transmitting the plurality of radiofrequency wave signals is executed such that an antenna pattern of the plurality of radiofrequency wave signals is oriented in a whole or semi- spherical pattern about the at least one autonomous vehicle; and such that theplurality of directional antennas remains in fixed positions during the step of transmitting the plurality of radiofrequency wave signals.

22. An object detection and avoidance system for at least one autonomous vehicle comprising: a plurality of directional antennas disposed about the at least one autonomous vehicle for transmitting and receiving radiofrequency wave signals; a multi-channel transceiver for pre-processing the radiofrequency wave signals received from the plurality of directional antennas, wherein each of the plurality of directional antennas is coupled to a channel of the multi-channel transceiver; each channel of the multi-channel transceiver comprising automatic gain control circuitry for range control of each channel based on a magnitude of a radio echo signal; and a controller connected to the multi-channel transceiver for controlling a collision avoidance maneuver of the at least one autonomous vehicle, based on radio echo signals received by the plurality of directional antennas from the at least one object.

23. The object detection and avoidance system of claim 22, wherein the plurality of directional antennas is a plurality of monopulse, fixed-beamwidth directional antennas; and wherein the plurality of monopulse, fixed-beamwidth directional antennas are positioned about a perimeter of the at least one autonomous vehicle at regular, angular intervals.

24. The object detection and avoidance system of claim 22, wherein the plurality of directional antennas is oriented in an overlap configuration such that a radiofrequency wave signal transmitted from each of the directional antennaspartially overlaps with the radiofrequency wave signal transmitted from at least one adjacent antenna of the plurality of directional antenna.

25. The object detection and avoidance system of claim 22, wherein each of the plurality of directional antennas includes an antenna shielding component for at least partially separating the radiofrequency wave signals transmitted by each of the plurality of directional antennas from one another; and wherein the antenna shielding component of each of the plurality of directional antennas is composed of a composite material that includes at least one layer of magnetic material, at least one layer of non-magnetic material, and at least one layer of surface current absorbing material.

26. The object detection and avoidance system of claim 22, wherein each channel of the multi-channel transceiver further includes at least one limiter element for limiting a power of the radio echo signal received by the one of the plurality of directional antenna, and a high-power protection element for switching off the channel of the multi-channel transceiver if the power of the radio echo signal received by the one of the plurality of directional antenna is above a predetermined power threshold.

27. The object detection and avoidance system of claim 22, wherein each channel of the multi-channel transceiver further includes at least one converter element for digitizing the received radio echo signals.

28. The object detection and avoidance system of claim 27, wherein the at least one converter element includes software defined radio circuitry, the software defined radio circuitry including a front-end circuit and an analog-to-digital converter.

29. The object detection and avoidance system of claim 27, further comprising synchronization circuitry connected to the controller and to each channel of the multi-channel transceiver for synchronizing the received radio echo signals.

30. The object detection and avoidance system of claim 22, wherein the controller includes a first control element for generating, based on the plurality of radiofrequency echo signals, a 3-dimensional map of the plurality of maneuver performance limitations of the at least one autonomous vehicle based on the received radio echo signals.31 . The object detection and avoidance system of claim 29, wherein the step of generating the 3-dimensional map of the plurality of maneuver performance limitations of the at least one autonomous vehicle further includes defining a 3- dimensional maneuver space of the at least one autonomous vehicle, the maneuver space defining one or more external limits of at least one direction of movement of the at least one autonomous vehicle.

32. The object detection and avoidance system of claim 26, wherein the controller includes a second control element that is programmed with computerexecutable instructions for detecting, via the plurality of directional antennas, at least one object based on a plurality of radiofrequency echo signals from the at least one object.

33. The object detection and avoidance system of claim 32, wherein the second control element is programmed with computer-executable instructions forestimating a relative position and velocity of at least one object based on the received radio echo signals.

34. The object detection and avoidance system of claim 33, wherein the controller includes a third control element that includes vehicle maneuver limitation logic data that defines a maximum degree of maneuverability of the at least one autonomous vehicle in at least one dimensions of motion, and collision risk logic data that defines a severity of outcomes for collision between the at least one autonomous vehicle and the at least one intruder vehicle.

35. The object detection and avoidance system of claim 34, wherein the third control element is connected to each of the first and second control elements within the controller, and wherein the controller is programmed with computer executable instructions for generating at least one collision avoidance maneuver for the at least one autonomous vehicle based on the 3-dimensional map of the plurality of maneuver performance limitations the vehicle maneuver limitation logic data and collision risk logic.

36. An object detection and avoidance system for at least one autonomous vehicle comprising: a plurality of directional antennas disposed about the at least one autonomous vehicle for transmitting and receiving radiofrequency wave signals; a multi-channel transceiver for pre-processing the radiofrequency wave signals received from the plurality of directional antennas; and a controller connected to the multi-channel transceiver for controlling a collision avoidance maneuver of the at least one autonomous vehicle, thecontroller including a computer-readable medium programmed with computer-executable instructions for: transmitting a plurality of radiofrequency wave signals via the plurality of directional antenna; detecting the presence of the at least one object based on a plurality of radiofrequency echo signals associated with the at least one object; generating, based on the plurality of radiofrequency echo signals, a 3-dimensional map of a plurality of maneuver performance limitations of the at least one autonomous vehicle; calculating a collision risk of the at least one autonomous vehicle and the at least one object, and generating at least one collision avoidance maneuver for the at least one autonomous vehicle based on the 3-dimensional map of the plurality of maneuver performance limitations and the collision risk.

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