US 20040024528 A1 Abstract A collision prediction and maneuver method determines which ones of many potential target objects have a close conjunction within a gross miss distance with a subject object by trajectory propagation, then determines which one of the conjunctive objects have a high collision probability within a critical miss distance, and then determines an optimum vehicle maneuver to reduce the probability of colliding with another colliding object by determining the maneuver direction, magnitude, and time so that the least amount of propellant is consumed while avoiding potential collisions within miss distance margins. The method includes computational efficiencies in collision probability calculations using trajectory propagations and contour integrations and efficiencies in optimum avoidance maneuvering using gradient and searching computations.
Claims(9) 1. A method for maneuvering a subject object for collision avoidance with a target object that may have a risk of collision at an approach time, the method comprising the steps of,
propagating backward trajectories of the subject object and the target object backward in time from the approach time, direction determining a maneuver direction of the subject object using a x-y-z conflict probability gradient of a conflict probability function where x-y-z directional partial derivatives of the x-y-z conflict probability gradient provide x-y-z directional decreases in a conflict probability for indicating the maneuver direction, and magnitude searching over maneuver magnitude values for an optimum maneuver magnitude by computing the conflict probability in the maneuver direction for each of the maneuver magnitude values and selecting one of the magnitude values as an optimum maneuver magnitude. 2. The method of 3. The method of 4. The method of 5. The method of maneuvering the subject object at one of the respective optimum maneuver directions and optimum maneuver magnitudes for avoiding collision with the target object.
6. The method of determining a maneuvering duration extending between a current time at current positions of the subject object and the target object, the maneuvering duration extending between the current time and a safety time when subject object approaches the target object to a safety distance, the propagated backward trajectories being backward propagated over the maneuvering duration divided into maneuvering duration time steps, the direction determining and magnitude searching steps being executed for each of the maneuvering duration time steps for providing respective maneuver directions and respective optimum maneuver magnitudes, and
maneuvering the subject object at one of the respective maneuver directions and at one of the respective optimum maneuver magnitudes for avoiding collision with the target object.
7. The method of applying a nominal magnitude along an x-axis and computing an x directional partial reduction in the collision probability,
applying a nominal magnitude along a y-axis and computing a y directional partial reduction in the collision probability,
applying a nominal magnitude along a z-axis and computing a z directional partial reduction in the collision probability, and
combining the x directional partial reduction and the y directional partial reduction and the z directional partial reduction into an x-y-z directional vector as the maneuvering direction.
8. The method of 9. A method for maneuvering a subject object for collision avoidance with a target object that may have a risk of collision at an approach time, the method comprising the steps of,
propagating backward trajectories of the subject object and the target object backward in time from the approach time, and direction determining a maneuver direction of the subject object using a x-y-z conflict probability gradient of a conflict probability function where x-y-z directional partial derivatives of the x-y-z conflict probability gradient provide x-y-z directional decreases in a conflict probability for indicating the maneuver direction. Description [0001] The present application is one of two related copending applications respectively entitled Vehicular Trajectory Collision Avoidance Maneuvering Method, Ser. No.: xx/xxx,xxx, filed yy/yy/yy, and entitled Vehicular Trajectory Collision Conflict Prediction Method, Ser. No.: xx/xxx,xxx, filed yy/yy/yy, having a common inventor. [0002] The invention relates to the field of collision prediction and avoidance of airborne and spaceborne moving vehicles. More particularly, the present invention relates to flight path trajectory conflict prediction and maneuvering avoidance methods for airplanes and spacecraft. [0003] Aircraft conflict prediction and resolution are performed manually by the pilots and air traffic controllers with the help of automated tools. The increase in air traffic is stressing the ability of the Air Traffic Management System to keep aircraft safely separated. Air traffic growth is expected to continue. The FAA Operation Evolution Plan is aimed at supporting a thirty percent overall growth in commercial aviation operations by 2010. Computer controller aids are expected to help relieve air traffic congestion. Such tools also enable free flight, which saves fuel and time. One such controller aid is the User Request Evaluation Tool, which is a conflict probe that looks ahead twenty minutes and helps en route controllers identify potential conflicts above 18,000 feet. Such tools require efficient computational methods to predict conflict. [0004] Aircraft are usually routed between way points with constant altitude, speed and heading. Heading corrections and throttle adjustments are made to prevent each aircraft from deviating too far off course. Nevertheless, navigation errors, uncertainty in winds and aircraft altitude result in position prediction error. These prediction errors were found to be Gaussian and can be represented by error covariance matrices. Between state vector updates, the error covariance matrices grow. Lateral errors are controlled to about ±1.0 nmi one sigma. Vertical error is roughly ±100 ft one sigma. Along-track errors grow at a rate of about ±15 nautical miles per hour between updates. During climb or decent, position uncertainty increases by an amount that depends on the details of the particular route being studied. Therefore, when aircraft routes are near each other, aircraft position uncertainty results in a probability of the aircraft coming within a specified keep out distance. If the probability value exceeds a threshold, a conflict is declared. A conflict can be resolved by maneuvering one or both of the affected aircraft. [0005] Predicting cumulative collision conflict probability for aircraft with constant velocity is very similar to space vehicle collision probability prediction. For aircraft, the probability of a conflict collision depends on the conflict volume, the relative position error, and the trajectories of the respective aircraft. First, one propagates the aircraft for thirty minutes. Next, coarse screening is performed to identify potential conflicts. Finally, collision conflict probability is predicted. The cumulative collision conflict probability method assumes that the relative velocity is constant and that the relative position error covariance matrix is constant during the encounter. These assumptions are not always valid, because aircraft routing involves turns at way points. In addition, along-track position errors grow between position data updates. The vertical position errors also grow during ascent or descent. Thus, a constant error covariance matrix throughout the encounter between the two aircraft produces uncertain risk of collision. The cumulative collision conflict probability formulation assumes both aircraft-were traveling from minus infinity to plus infinity. This assumption can result in small errors in the collision probability. A slight increase in the predicted collision conflict probability could result. For these reasons, a general formulation for collision conflict probability is needed. [0006] A conventional conflict keep-out box is a conflict volume that may be a cylinder 5.0 NMI in radius and 4,000 ft in height for aircraft flying above 29,000 ft. For aircraft flying below 29,000 ft, the cylinder height is reduced to 2,000 ft and a conflict occurs for aircraft with less than 5.0 NMI separation having altitudes that differ by less than ±1,000 ft. The cylinder is centered on the flying aircraft and oriented vertically with its height corresponding to altitude. Thus, when an aircraft is predicted to come within 5.0 NMI lateral distance or ±2,000 ft vertical distance, a conflict exists. The time of conflict resolution is a tradeoff between efficiency and error uncertainty. When the maneuver is too far in advance, it is efficient and therefore smaller but growth in position uncertainty reduces confidence in the computed collision conflict probability. When the maneuver is not far enough in advance, confidence in the computed collision probability is high but less time is available for the maneuver to avoid the conflict and a larger less efficient maneuver must be made. Thus, there is an optimum maneuver time to resolve a conflict efficiently. The ability to predict conflicts efficiently is needed to help air traffic controllers. [0007] In level flight, the conflict determinations can be partitioned into vertical and horizontal portions because the cylindrical conflict volume is symmetric in the horizontal plane and there is no cross correlation between vertical and horizontal errors. The probability density is integrated from minus infinity to plus infinity along the relative velocity direction. The result is always unity because the probability density is normalized. The resulting two dimensional integral can be partitioned into two separate error function integrals with limits defined by the dimensions of the conflict cylinder. Thus, the conflict probability reduces to the product of two error function integrals. [0008] Vertical and horizontal errors are correlated in the case of non-level flight. In addition, the cylindrical conflict volume takes a more complex shape when the conflict volume is projected to an encounter plane, which is normal to the relative velocity. An approximate solution and a Monte Carlo simulation approach has been proposed to overcome the difficulties of computing conflict probabilities for more complex shapes of the keep-out volume. The computational requirement is significantly greater with the Monte Carlo method. Although the FAA is currently modernizing the traffic control system by increasing automation, effective computerized methods to predict aircraft conflict and avoidance maneuvering are needed. [0009] Collision conflict prediction methods have been used to determine when a spaceborne or airborne vehicle is likely to have a significant collision risk with another object. A contour integration method has already been used on asymmetric space vehicle collision probability and collision probability for space tethers. When there is a significant collision risk, it is then desirable to perform a collision avoidance maneuver prior to the collision time for both aircraft and spacecraft. Spacecraft collision avoidance is also becoming an increasing concern as the number of space objects continues to increase over time. There are currently over 9,500 tracked orbital objects. The need for collision avoidance maneuvers is correspondingly increasing as the number of operational satellites and associated debris objects increase. The narrow altitude bands associated with communication satellite constellations in both low earth orbit and geosynchronous earth orbit requires improved collision prediction and avoidance methods because satellites occupying the same altitude range have increased risk of collision. The collision hazard posed by debris and other operational satellites has been increasing to the point where collision avoidance maneuvers should be considered as a means to mitigate the collision risk. The increasing collision hazard is forcing manned vehicles to perform unwanted collision avoidance maneuvers. Such maneuvers are disruptive to mission operations. For example, the Space Shuttle performs a maneuver, when the predicted miss distance is less than two kilometers radially, five kilometers in-track and two kilometers out-of-plane. The International Space Station has already performed two collision avoidance maneuvers based on collision probability predictions. Collision avoidance maneuvers for space vehicles reduce vehicular life span due to propellant consumption while additional thruster firings increase the potential for propulsion system failure. The decision to perform a collision avoidance maneuver is based on a cost-risk analysis that requires a quantifiable measure of risk. Unlike a keep-out box criterion, collision probability provides the needed quantification of risk. Collision probability can be weighed against the propellant consumed and shortened operational life span of the space vehicle. The value of the space asset can be used to establish a collision risk threshold. Because the amount of propellant is directly related to an operational lifetime and revenue of a satellite, maneuvers should be performed in the most efficient and effective manner possible. This requires searching a four-dimensional space for an optimal solution. This space consists of the time of application, velocity magnitude and direction, right ascension and declination, of the applied maneuver. Computational efficiencies in propagation, collision probability calculation and optimization are required to allow sufficient time for maneuver planning. [0010] The maneuver is made to reduce the collision risk to an acceptable level. The most effective maneuver is one that requires minimum maneuver velocity and associated propellant. There are three components necessary to determine the most effective maneuver: maneuver time, maneuver direction, and maneuver magnitude. These components need to be determined expeditiously so that enough time is allowed for performing operational tasks required to implement the maneuver. Hence, there exists a need to timely determine the optimal maneuver for avoidance of a pending collision. Numerical methods have been used for conflict avoidance and maneuvering, but the numerical method often required more time to predict a collision and maneuver than is available during a pending collision. These and other disadvantages are solved or reduced using the invention. [0011] An object of the invention is to provide a method for predicting potential collisions. [0012] Another object of the invention is to reduce risk to a subject object from collision with one or more target objects. [0013] An object of the invention is to provide a method for screening target objects for those that come within an approach distance to a subject object for indicating a possible collision conflict. [0014] Another object of the invention is to provide a method for determining a conjunction between a target object and a subject object when the separation distance is within a critical distance through high fidelity trajectory propagation for indicating a probable collision conflict. [0015] Yet another object of the invention is to provide a method for determining a collision conflict probability of a collision between a subject object and a target object through high fidelity trajectory propagation, through coordinate rotation and scaling based on error covariance matrices, and through contour integration. [0016] Another object of the invention is to provide a method for determining an optimum maneuver including a maneuver time, maneuver direction, and maneuver magnitude of a maneuvering subject object for avoiding a collision with a target object through a gradient method and a root finding method. [0017] The invention relates to collision prediction and collision avoidance maneuvering. The invention method determines risk of a potential collision between a subject object and a target object, and determines an optimum maneuver to avoid potential collision. The subject object may be an aircraft, an orbiting spacecraft, a launch spacecraft, or a free space traveling spacecraft. The target object may be one of many target objects that may also be an aircraft, an orbiting spacecraft, a launch spacecraft, a free space traveling spacecraft, space debris, or airborne debris. [0018] The method first determines when the subject object will come within a large approach distance for screening target objects that have an impossible collision conflict with the subject object. For those target objects that do not have an impossible collision conflict, the method then determines whether the closest approach separation distance between the subject object and the target object will be less than a critical distance for determining a conjunction through trajectory propagations. Conjunction determinations use high-fidelity time-stepped trajectory propagation. [0019] When it is determined that a target object will have a conjunction with the subject object, then the method determines the collision probability between the subject object and the target object. The collision probability is a risk of a potential collision. The collision probability determination uses an error covariance matrix that is transformed to an encounter frame by rotation and scaling. In the encounter frame, a contour integration method is used for efficient computation of collision conflict probability. When a target object will have a collision conflict probability with the subject object above a predetermined collision conflict probability threshold, that is, above a predetermined risk value, then a maneuver may be executed for collision avoidance. [0020] When the subject object will have collision conflict probability above the predetermined collision conflict probability, indicating a need for maneuver avoidance, the method then determines an optimum maneuver, in terms of maneuver direction, maneuver magnitude, and maneuver time so as to reduce the collision conflict probability below the predetermined probability for reducing risk of collision. The direction and magnitude of the maneuver velocity is found in two steps. The direction is found by using a gradient method, which determines the maneuver direction that results in the largest reduction in collision probability for a given maneuver velocity magnitude. Once the direction is found, the maneuver magnitude is found by using a search method, such as a Secant root or Newton root search method that lowers the collision probability to below the collision probability threshold. A maneuver choice can be made from the selection of optimal maneuvers from maneuver options. When a maneuver is required, a maneuver duration is selected for indicating possible maneuver times prior to the conjunction. For each time step during the maneuver duration, the optimum maneuver is found that reduces the collision probability. The optimum maneuver is determined in a computationally efficient manner that requires negligible amounts of time. This efficient computation allows sufficient time for planning the maneuvers. [0021] The method uses various processes, including conjunction determinations through trajectory propagation, collision probability prediction through coordinate rotation and scaling based on error covariance matrices, and numerical searching for optimum avoidance maneuvers. Significantly, the collision probability calculation is performed using an enhanced contour integration method for rapid computation. The maneuver avoidance method determines the effect of a vehicular maneuver on the collision probability by propagating the vehicle from the potential collision time backwards to the maneuver time, and then applying the maneuver and propagating the vehicle forward in time to the potential collision time. Significantly, the maneuvering direction is determined using a gradient method. The propagation is analytically performed using either conventional Keplerian two-body mechanics or high fidelity trajectory propagation. [0022] The method is applicable to aircraft having level, turning, ascending and descending flight paths, and spacecraft having orbital flight paths, launch vehicles having launch paths, or spacecraft having free space flight paths. Collision probability for aircraft has inputs including altitude position, speed and direction, and safety keep-out volumes. Spacecraft use a hard-body volumes for collision probability and aircraft use a keep-out volume for conflict prediction, but herein, both nomenclatures are mathematically treated the same for collision probability computations. [0023] Collision probability prediction for spacecraft has inputs including the respective state vectors, error covariance matrices, and physical sizes of the subject and target objects with the sizes being used as safety keep-out volumes. Because the relative velocity of orbital objects at the closest approach is very large compared to the relative accelerations, the relative velocity is considered constant during the encounter period of closest approach. When more than one collision is possible for the subject object, such as for orbital bodies having cyclic orbits, the cumulative collision probability is used in place of the single collision probability. The cumulative collision probability is the sum of collision probability for each potential collision. The method enhances the ability to predict potential collisions and to determine avoidance maneuvers in a timely manner so as to avoid collision. This would enable operational collision risk of aircraft and spacecraft to be reduced in an automated manner. These and other advantages will become more apparent from the following detailed description of the preferred embodiment. [0024]FIG. 1 is a conflict prediction and avoidance maneuvering process. [0025]FIG. 2 is a contour integration diagram. [0026]FIG. 3 is a probability and miss distance graph. [0027]FIG. 4 is a maneuver velocity magnitude graph. [0028]FIG. 5A is a level flight conflict probability graph. [0029]FIG. 5B is a descending flight conflict probability graph. [0030]FIG. 6A is an aircraft relative trajectory graph. [0031]FIG. 6B is an aircraft probability graph. [0032] An embodiment of the invention is described with reference to the figures using reference designations as shown in the figures. Referring to FIG. 1, the method is generally divided into three processes that determines conjunctions, collision probabilities and avoidance maneuvers. The method determines possible conjunctions in steps [0033] A tracking data catalog [0034] The subject object may have potential collisions with several respective target objects. Of all of the cataloged target objects in the tracking data catalog [0035] The screening process [0036] The screening process [0037] The high fidelity trajectory propagation [0038] The high fidelity trajectory propagation [0039] The trajectory propagation duration is determined [0040] At each time step of the high fidelity trajectory propagation, the separation distance between the subject object and target object is determined from the initial time to the current time of high fidelity trajectory propagation. As the subject object and target object are propagated in time forward, the separation distance is computed at each trajectory propagation time step. Conjunction determinations [0041] Referring to FIGS. 1 and 2, after a conjunction is declared [0042] The propagated positions, propagated velocities, and the propagated position error covariance matrices from the high fidelity trajectory propagation [0043] The error covariance matrices for the subject object and the target object are transformed [0044] The combined error covariance matrices are in a common reference frame that is relative to the respective initial reference frames. A rotational matrix is used for rotating the combined error covariance matrices in the common reference frame into diagonal error covariance matrices in a diagonal reference frame at each of the approach trajectory duration time steps. A scalar matrix is used for scaling the diagonal error covariance matrices in the diagonal reference frame into scaled error covariance matrices in the scaled reference frame at each of the approach trajectory duration time steps. The transformation process [0045] The propagated trajectory positions and velocities for the subject object and target object are vectors, and the conflict volume is a vector of surface points. The respective propagated positions, respective propagated velocities, respective conflict volume, the transformation matrix, rotational matrix, and the scalar matrix, are used to transform [0046] The scaled positions, scaled velocities, scaled keep-out box, and scaled error covariance matrices in the scaled reference frame are aligned [0047] An incremental collision probability at each approach trajectory duration time step is computed [0048] The incremental collision probability for each approach trajectory duration time step is found by multiplying the z-axis incremental probability by the x-y plane incremental probability. The incremental collision probabilities for each approach trajectory duration time step is accumulated [0049] The error covariance matrices are combined, rotated and scaled [0050] A collision probability threshold is selected [0051] A general formulation requires an ability to compute the instantaneous rate of collision conflict probability for each approach trajectory duration time step. The position, velocity and error covariance matrix for each object is propagated to each approach trajectory duration time step. Total collision probability can be computed by accumulating the incremental probabilities or equivalently by using the incremental probability time rate of change. The incremental probability rate of the incremental collision probability for each time step is calculated by dividing the incremental collision probability by the time step duration. The total probability of conflict over a specified time is obtained by integrating the incremental collision probability rate over the approach trajectory duration time [0052] The collision probability method of steps [0053] If the keep-out box and respective velocities, error covariance matrices of the subject object and the target object in the combined reference frame are constant, then the accumulative collision probability is equal to the x-y plane incremental probability. In this case, the x-y plane incremental probabilities for each approach trajectory duration time step are equal and the cumulative collision probability is equal to the product of the x-y plane incremental probability and the sum of the z-axis incremental probabilities. The sum of the z-axis-incremental probabilities equals one because the z-axis probability function is normalized to unity. The accumulative collision probability [0054] Aircraft collision probability, that is, conflict probability can be computed using contour integration. Three factors that affect aircraft collision conflict probability include aircraft trajectory, position error covariance matrices, and conflict volume shape. During aircraft turns and ascent and descent conditions, aircraft trajectory and position error covariance change as a function of time. The time dependence is accounted for by dividing the approach trajectory into the approach trajectory duration time steps and computing the incremental collision probability at each time step. The cumulative collision probability is found by accumulating the incremental collision probabilities for each approach trajectory duration time step. Position error covariance matrices and the relative velocities is assumed constant during each respective time step. However, error covariance matrices and relative velocities can be different for each approach trajectory time step. The cumulative collision conflict probability is found by adding the incremental collision conflict probability associated with each approach trajectory duration time step over approach trajectory duration. In this manner, the cumulative collision conflict probability [0055] The position and velocity of each object is transformed into the scaled coordinate reference frame. The relative position and velocity in the scaled coordinate frame are used to define the encounter reference frame. The encounter frame has the z-axis aligned with the relative velocity vector and the x-axis perpendicular to the z-axis and clocked to align with the relative separation vector. The conflict volume of the keep-out box of FIG. 2, which is assumed centered about the target object is transformed into the inertial frame and then to the encounter frame. Because the probability density is symmetric, the probability density along each axis is decoupled from the other axes in the encounter reference frame. The polar radial coordinate r is integrated directly, thus reducing the three-dimensional contour integral into a one-dimensional contour integral about the keep-out box
[0056] The coordinate transformations are needed to transform the positions, velocities, error covariance matrices and conflict volume for an object into the scaled reference frame for each approach trajectory duration time step. Because the error covariance matrices are defined in the initial reference frame of each aircraft, the error covariance matrices are transformed into the common reference frame. The transformations from local to inertial frame for each object are given by P [0057] In the C [0058] The relative error covariance matrix C [0059] The relative position and velocity in the inertial frame are respectively given by {right arrow over (X)}={right arrow over (r)} [0060] The cumulative collision conflict probability is given by a cumulative collision conflict probability equation.
[0061] The limits of integration in the cumulative collision conflict probability equation are defined by the volume swept out by the conflict cylinder in the encounter frame. Because z is in the direction of relative velocity, it is convenient to transform to cylindrical coordinates with the z-axis aligned with the cylinder axis. The cumulative collision conflict probability equation becomes a revised cumulative collision conflict probability equation.
[0062] The r integration can be performed immediately, yielding a modified cumulative collision conflict probability equation.
[0063] The closed path contour is about the perimeter of the keep-out box area in the encounter plane. When the relative velocity and relative error covariance are constant throughout the encounter, the bracketed term in the modified cumulative collision conflict probability equation is equal to one and the cumulative collision conflict probability is given by a simplified cumulative collision conflict probability equation.
[0064] When the relative velocity or the relative error covariance change, the incremental collision conflict probability is obtained by an incremental collision conflict probability equation.
[0065] The simplified cumulative collision conflict probability equation can be used in the incremental cumulative collision conflict probability equation to obtain a revised incremental collision conflict probability equation.
[0066] Because both dz and σ(1) are permitted to change during the encounter, it is useful to define the non-dimensional parameter λ, which is defined by λ=z/σ(1). The revised incremental collision conflict probability equation can be rewritten as a PR [0067] The collision conflict probability rate can now be obtained by dividing the modified incremental collision conflict probability equation by the time increment associated with dλ to obtain a PR [0068] The collision conflict probability rate is evaluated for each approach trajectory duration time step. The collision conflict probability rates are integrated over the approach trajectory duration time t [0069] The accumulative probability equation is preferably used for x-y plane accumulative probability computations for straight line flight path segments for maneuvering spacecraft and aircraft maneuvers, such as turns at way points and descent or ascent maneuvers. [0070] Contour integration of step [0071] The position and velocity of each object is transformed to the scaled reference frame. The relative position and velocity in the scaled coordinate frame are used to define the encounter frame. The encounter frame has a z-axis aligned with the relative velocity vector and an x-axis perpendicular to the z-axis that are rotated for alignment of the z-axis with the relative velocity vector with the keep-out box being centered about the target object in the encounter frame. [0072] A subject object is located at the origin of the encounter frame, which is also the center of the relative position error probability density. The conflict volume is centered on the target object, which is displaced from the origin by a distance determined by the closest approach. Points defining the shape of the conflict volume are transformed into the keep-out box in the encounter plane. These points are used in the evaluation of the contour integral. The points are enumerated sequentially in a counter clockwise direction about the perimeter. The angle between the two adjacent vectors, X [0073] In the dθ [0074] The integral is evaluated by summing values of the integrand times dθ [0075] Once one complete cycle about the keep-out box is made, the cumulative probability is given by the simplified cumulative probability equation, as PR [0076] The keep-out box in the encounter plane for horizontal flight is approximated by a rectangular box in a y by x scaled frame. During aircraft descent, the conflict volume cross section changes as a bulging rectangle. During descent, the vertical position uncertainty increases a greater percentage than the horizontal position uncertainty. Thus, the height of the scaled conflict volume decreases over time. The keep-out box in the encounter plane for descending flight is approximated by a rectangular box in a y by x scaled frame with the vertical sides of the rectangular box bulging outwardly. For a level flight for both aircraft during an encounter with a 5.0 nmi closest approach distance, the error covariance matrix was held fixed for each aircraft. The collision conflict probability is a function of time throughout the encounter. The collision conflict probability rate peaks at the time of closest approach. The collision conflict probability and collision conflict probability rate is a function of time for constant relative error covariance. [0077] Avoidance maneuvering process of steps [0078] The high fidelity state vectors of both objects propagated to the point of conjunction are retained and used as initial condition for forward and reverse Keplerian two-body propagation for reduce computational requirements based on the recognition that the maneuvers will be small and will produce small trajectory changes. A maneuver typically displaces the position of the subject object at the conjunction point to achieve the necessary reduction in collision probability. Changes in the trajectory due to a small maneuver are typically small enough to render all higher order contributions from orbital perturbations negligible with respect to collision probability. [0079] A maneuvering limitation determination [0080] A maneuvering duration is selected [0081] Once the maneuvering duration and maneuvering time steps are determined [0082] After the optimum maneuver direction is found, for a given maneuver duration time step [0083] The maneuvering directions and maneuvering magnitudes are determined [0084] The maneuver direction is one that reduces the collision probability most effectively. The gradient method finds the optimal maneuver direction using trajectory propagations and collision probability calculations associated with the maneuver trajectory direction. The maneuver direction is an optimum maneuver direction. The maneuver direction is computed based on an assumed low magnitude thrust. If the magnitude is large, the direction can be recomputed, due to nonlinear gravitational affects. The gradient method examines the change in normalized partial derivatives of the collision probability along the three axis to select a direction with the maximum lowering of the collision probability. The maneuver magnitude selection preferably uses a root searching method, such as well known Newton Root and Secant Root search methods. [0085] The maneuver magnitude is a maneuver velocity vector that most effectively lowers the collision probability to below the maneuver threshold. Hence, collision probability can be recomputed based on maneuver magnitude at the determined maneuver direction. A Secant root finding method is used to determine the optimum maneuver magnitude using trajectory propagation and collision probability associated with the new maneuver trajectory. [0086] The maneuver time, the optimal maneuver direction, and the optimal maneuver magnitude are compiled as maneuver directions and maneuver magnitudes over the maneuver duration time steps, which can be represented in graphic form, such as a plot of maneuver velocity versus maneuver time. One of the possible maneuver times, and respective maneuver directions and maneuver magnitudes are analyzed and one is selected as the best one of the optimum maneuvers. The selection method selects one of the maneuvers from the current time. The selection method can be, for example, one selects the maneuver that uses the smallest amount of fuel to reach a collision probability equal to the predetermined probability threshold, or one that reduces the collision probability to a minimum value. [0087] For each time, the optimum maneuver velocity direction and magnitude is found that reduces the collision probability to the maneuver threshold. This search entails propagating the state vectors backward from conjunction to the maneuver time, applying the maneuver and propagating the state vectors forward to the new conjunction time. A gradient method [0088] In the {right arrow over (G)} gradient vector equation, the terms x, y, z are velocity components and are defined in the local coordinate frame, with z being opposite to the radial vector, y being opposite to the angular momentum vector and x completing the right handed system. The size of the velocity increments used in evaluating the gradient can be adjusted for the nature of the problem being solved. A velocity increment of approximately one cm/sec was found acceptable for several cases involving geostationary satellites. The magnitude of the maneuver velocity [0089] Satellite operational constraints can limit the maneuver direction. In such cases, the gradient is modified appropriately and the maneuver velocity magnitude is found in the same way. FIG. 4 illustrates a case where the maneuver velocity is limited to posigrade or retrograde velocity increments. The magnitude of maneuver velocity is plotted as a function of time prior to the original conjunction. When compared to the magnitude of the maneuver velocity for a fully three-dimensional maneuver significant differences exist when the maneuver is applied close to the time of conjunction. The maneuver direction is initially in the forward or reverse direction when the maneuver time is far from conjunction. As the maneuver time approaches conjunction, the three-dimensional maneuver direction changes into a direction having a progressively larger nadir component. A satellite operator can select the maneuver time [0090] The selected maneuver that reduces the risk of a space vehicle colliding with another space object was developed. For a specified time prior to conjunction, a maneuver is found that will reduce the collision probability or the cumulative collision probability, to below a predefined probability threshold [0091] The most fuel-efficient maneuver is selected so as to reduce the collision probability below a prescribed threshold [0092] Referring to FIG. 3, the probability for each of several identified conjunctions between the two vehicles is computed. For this case, there were no conjunctions between the subject object and any other object except the target object. The run length was 14 days and there were no conjunctions prior to 3 days. The cumulative probability of collision was 7.74 e [0093] Referring to FIGS. 5A and 5B, collision conflict probability depends on the amount of time between aircraft state vector update and the time of closest approach because the position error covariance grows linearly in the in-track direction. FIG. 5A shows collision conflict probability corresponding to the target aircraft shown in FIG. 5B descending at 1,500 ft per minute. FIGS. 5A and 5B illustrate the collision conflict probability as a function of time to the closest approach for several closest approach distances. Only the z-axis error covariances of the error covariance matrices increased, because level flight was assumed for these cases for the subject aircraft. The increase in probability for the larger closest approach distances reflects the significant growth in the relative position error. Aircraft descent affects collision conflict probability. For example, during a descent of 1,500 ft per minute, the one-sigma z-axis position error increases at a rate of 0.333 nmi per minute. The one-sigma y-axis position error increases at 300 feet per minute. The target aircraft began descending seven minutes before closest approach until seven minutes after closest approach. The initial altitude of the target aircraft is adjusted so that the vertical separation from the subject aircraft is zero at closest approach. The collision conflict probability is found for state vector updates at various times for several closest approach distances. The effect of increasing relative position error is due to the aircraft descent. [0094] Referring to FIGS. 6A and 6B, the method predicts collision conflict probability for aircraft turns at waypoints as well as ascent and descent flight conditions and level flights. An aircraft turn affects the collision conflict probability by changing the relative velocity and encounter frame. The target aircraft makes a turn, with each aircraft having a speed of 300 knots. The one-sigma z-axis position error starts at 0.25 nmi and grows linearly at a rate of 0.25 nmi per minute. The one-sigma x-axis position error is assumed fixed at 2.0 nmi. The one-sigma y-axis errors are fixed at 100 feet. The target aircraft has the state vectors updated at initiation of the encounter and executes an instantaneous 45 degree right turn at a specified time prior to closest approach, which occurs at 600 seconds. FIG. 6A illustrates the relative trajectory with turns at 95 and 300 seconds from closest approach. The closest approach distance is zero for the turn executed at 95 seconds. Each trajectory represents 1200 seconds. The turn trajectories appear truncated because the relative velocity magnitude decreases due to the turn. FIG. 6B illustrates the collision conflict probability as a function of turn time. The maximum probability occurs at 95 seconds, which also corresponds to the minimum closest approach distance. [0095] Operational maneuver planning can be complicated by the avoidance maneuver. For instance, consider a vehicle that is facing several conjunctions, but only one of which is dangerous and warrants a maneuver. Then, once a maneuver solution is found that reduces that conjunction to a safe level, care must be taken to make sure the final burn solution does not significantly increase the collision risk with any other conjunctions. Some operational considerations enter the decision-making process regarding the selection of the actual burn to be performed. In general, it is better to conduct probability reduction maneuvers in terms of fuel efficiency as far in advance of the dangerous conjunctions as possible. However, state vector information is constantly updated and the target object, if it is an active vehicle, may undergo its own stationkeeping or operational maneuvers that will invalidate an early burn solution. Therefore, it may be at times advisable to wait until the conjunction is imminent before conducting a burn for the subject object. [0096] A maneuver is selected that will reduce the risk of a space vehicle colliding with another space object. For a specified time prior to conjunction, a maneuver is found that will reduce the collision probability to a predefined maneuver threshold. In this manner, the maneuver magnitude and space vehicle propellant required can be minimized, thereby extending space vehicle life. The method provides computational efficiencies in orbital propagation, collision probability prediction, and maneuver optimization. Those skilled in the art can make enhancements, improvements, and modifications to the invention, and these enhancements, improvements, and modifications may nonetheless fall within the spirit and scope of the following claims. Referenced by
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