Fault-tolerant inertial navigation system

Abstract: Disclosed herein is a Fault-Tolerant Inertial Navigation System (70) comprising, in a preferred embodiment, a Redundant Set of at least two Inertial Navigation Systems (101, 102) from which one may identify and isolate at least one instrument within an Inertial Navigation Unit which shows substantial performance degradation. The two inertial navigation units are fully capable of performing navigational functions. Each of these inertial navigation units has a plurality of navigational instruments, including at least three linear sensors (such as accelerometers) (38) and three angular change sensors (such as gyroscopes or ring laser gyroscopes) (32, 34, 36). No two linear sensors nor any two angular change sensors of either unit are aligned collinearly. Each of the inertial navigation units produces a set of independent navigational solutions (X₁, X₂) at each of their respective outputs. The independent navigational solutions of each of the navigation units are compared and any significantly degraded performance of any one linear sensor or any one angular change sensors is detected.

Description: This invention relates to Inertial Navigation, and in particular to a Fault Tolerant system for Inertial Navigation which identifies and isolates at least one instrument within an Inertial Navigation Unit which shows substantial performance degradation. Navigation is the process of spatially directing a vehicle (Land, Sea, or Aircraft) from a first point (or point of origin) to another or second point in space. Navigation is often categorized as either position fixing or dead reckoning. Examples of position fixing include celestial navigation or determining one's position with respect to known objects or landmarks. LORAN and related radar systems, and the newer NAVSTAR GPS (Global Positioning System) are also examples of position fixing Navigation. Generally speaking, dead reckoning is the process of estimating ones position by knowledge of one's previous position, his course, his speed and the elapsed time. This category of dead reckoning includes doppler Radar and Inertial Navigation Systems. Inertial navigation is yet further unique, in that it is a specialized form of Navigation whereby one is able to travel from point one to point two without the benefit or need of any information external to the vehicle. Inertial Navigation is completely self-contained within the traveling vehicle. Inertial Navigation is independent of its operating environment such as wind, visibility, or aircraft attitude. Because such form of Navigation does not radiate RF energy, it is immune to countermeasures. Inertial Navigation makes use of the basic laws of physical motion first described by Sir Isaac Newton over three centuries ago. A standard Inertial Navigation System (INS), in actual use, such as aboard commercial or military aircraft, often comprises three or more independent inertial navigation units, where each unit is composed of 3 accelerometers and 3 gyroscopes so that each unit alone is fully capable of performing the navigation function. Three INU's (Inertial Navigation Units) or more represents a costly method to assure redundancy and accuracy of navigation. An early attempt to provide redundancy in less than three INU's is U.S. Patent 3,489,004, issued January 13, 1970 to D.H. Barnhill et. al. for a NAVIGATIONAL REFERENCE DEVICE (Honeywell, Inc. Assignee). This patent teaches the use of at least four sensor mechanical gyroscopes in each INU mounted to an attitude reference device base unit. When one of the gyroscopes of the INU is faulty, the remaining gyroscopes may be used to function as an INU. Thus, in this reference '004 patent, redundancy is provided within each INU and independent of other INU systems. Such a scheme might be applied to a Ring Laser Gyroscope instrument package, but ring laser gyroscopes are typically one-degree of freedom devices and these ring laser INU's generally are packaged with only sets of three instruments, three gyroscopes and three accelerometers. Another redundancy scheme demonstrated heretofore can be found in U. S. Patent 3,680,355 issued August 1, 1972 to Goldstein et. al. for METHOD AND APPARATUS FOR PERFORMANCE MONITORING OF DUAL PLATFORM INERTIAL NAVIGATION SYSTEMS (The Singer Company, assignee). In this '355 patent, two platforms are used to provide the required redundancy; however, each platform uses two, two-degree of freedom, mechanical gyroscopes to provide adequate redundancy. This is the equivalent of using at least four ring laser gyroscopes and again would be costly. IEEE PLANS 86 SYMPOSIUM RECORD, 4-7 Nov. 1986, Las Vegas, NV, USA, page 445-455 also discloses redundant inertial units, in that case with two identical units each with redundant gyroscopes and accelerometers, i.e. each unit requires four gyroscopes and four accelerometers with no constraint upon the relative orientation of the units. An alternative approach is described in JOURNAL OF SPACECRAFT AND ROCKETS, vol. 9, no. 1, January 1972, NEW YORK US pages 39-47, in which a single unit or platform supports twelve sensors, six gyroscopes and six accelerometers, arranged with no common axes, i.e. their axes are normal to respective faces of a dodecahedron. Consequently, each sensor provides a measure of redundant data so that it is possible to identify and isolate failures up to a certain point. An improvement of the prior art needing only two navigational units is achieved with an inertial navigation system according to claim 1. For a better understanding of the invention and to show how the same may be carried into effect, reference will now be made, by way of example, to the accompanying drawings, wherein: Figure 1 is a perspective schematic view of the Aircraft Installation Configuration of the Two Inertial Navigation Instrument Assemblies (INA); Figure 2A is a perspective view of the configuration of the two Inertial Navigation Instrument Assemblies of this Invention as these assemblies are configured during flight within their respective system boxes. Figure 2B is an end view of the configuration shown in Figure 2A. Figure 3 is a schematic drawing of the PRIOR ART configuration of a navigation redundancy system. Figure 4 is a schematic drawing of the Fault Tolerant Inertial Navigation system according to one embodiment of this invention. Figure 5A is a schematic drawing showing how the Fault Detection and Isolation Logic system interact with the Inertial Navigation Systems. Figure 5B is a detailed schematic drawing showing how the Fault Detection and Isolation Logic system estimates error with respect to the Inertial Navigation Systems parameters. One embodiment of the invention employs a method of comparison of the navigation solutions between the 2 independent navigation units such that, in the event that the performance of one gyroscope and/or one accelerometer degrades significantly ("soft" failure) or fails in one unit, this instrument is identified (isolated) as being faulty. In the prior Art configuration, as schematically shown in Figure 3, at least three (3) separate and redundant Inertial Navigation Systems (INS) 62, 64, and 66 are needed to provide information to a pilot (through the Flight Management Computer 60) as to the identification of a substantially degraded Navigational Instrument. When such a degraded Navigational Instrument is identified, through use of the triple redundancy and voting, the entire INS is discounted. In contrast to the prior Art embodied in Figure 3, the present invention has the ability to identify and isolate a degraded Instrument using only two Inertial Navigation Systems 72 and 74 (see, Figure. 4). In order for the Fault Tolerant Inertial Navigation system 70 disclosed in Figure 4 to properly function, it is useful to examine Figure 1, 2A, and 2B to see how each Inertial Navigation System's instrument packages 30 and 44, respectively, are configured. With reference to Figure 2A, one will note that upon the instrument block 40 is mounted at least three single degree of freedom angular rate sensors, preferably ring laser gyroscopes 32, 34 and 36. The gyroscopes 32, 34 and 36 are oriented along respective directions which are orthogonal to one another. Also mounted on the instrument block 40 are at least three accelerometers (accelerometer 38 being visible schematically in Figure 2A). Like the angular rate sensors 32, 34 and 36, the linear sensors, such as accelerometer 38, are oriented along respective directions, normally corresponding to the same axes about which the gyroscopes 32, 34 or 36 are mounted. For example, the accelerometer 38 is oriented along the same direction or axis as gyroscope 34. Likewise, accelerometers 94 and 96 are mounted on instrument block 90 and oriented along the respective axes of gyroscopes 54 and 56. In order to allow the Fault Tolerant Inertial Navigation system 70 to operate, it is important that the axes 18 and 20 (Figure 1) of the Inertial Navigation systems 14 and 16 are oriented such that none of the three directions in each system is colinear. In order to achieve this requirement, one may orient each instrument package differently, such as the manner in which axes 18 and 20 are oriented. All the axes of the two systems are 60° apart from one another (about the Y-axis). This is illustrated in Figures 2A and 2B where when one lines up the two instrument blocks 40 and 90 along parallel axes 50 and 50'; it will be noted that the instruments affixed to the block 90 are rotated 60° with respect to one another (rotation 42 about axis 50'). None of the sensing axes of measurement of any of the gyroscopes 32, 34 or 36 (Figure 2A) align with any of the gyroscopes 52, 54 or 56 (Figure 2B). By mounting the systems 14 and 16 backward with respect to one another (Figure 1) (along mounting directions 22 and 24), the 60° rotation of orientation is automatically achieved and measuring axes are in alignment. To obtain this capability no individual accelerometer of one navigation unit is approximately colinear with an individual accelerometer sensing axis of the other navigation unit and no individual gyroscope sensing axis of one navigation unit is approximately colinear with an individual gyroscope sensing axis of the other navigation unit. Comparison of the navigation solutions obtained by the two navigation units can be done at either the computed vehicle position, computed vehicle velocity or computed vehicle orientation level or any combinations of these levels. With reference to Figure 4, assuming that none of the measuring axes of the instruments is aligned, output variables of X 1 and X 2 are provided by the INS 72 and 74 for the same measured parameter (such as orientation, velocity and/or position). The system 70 then combines these variables X 1 and X 2 at a difference node 76 and the difference is then processed by Kalman Filters 78 and 80 in real time according to algorithms known in the art to provide an estimate of the accuracy of each output signal and other modeled error parameters. At the outputs 82 and 84 of the filters are presented respective sets of error estimate values as error estimate vector quantities ê 1 and ê 2 , from which a determination can be made whether the instruments in each system 72 and 74 are working properly, and, if not, an identification of the location of the defective instrument, in either system 72 and 74, can be determined. In this manner, a fault tolerant inertial navigation system is derived. The differences in the compared computed quantities (position, velocity and/or orientation) are processed by an optimal estimation (Kalman filter) algorithm which includes as its error states the errors in the computed navigation variables (position, velocity, orientation) and appropriate error states for the inertial instruments, including for example individual gyroscope and accelerometer biases, scale factor errors, mounting misalignments of the accelerometers and gyroscopes within each navigation unit with respect to each other and mechanical misalignments between the two navigation units. The pattern of differences between the navigation solutions of the two navigation units will, in the event of degraded performance or failure of one accelerometer and/or gyroscope in either navigation unit, result in a large (relative to nominal expectations) estimate of the error parameters of that instrument (for example a gyroscope) in the degraded navigation unit via the Kalman filter processing. On the other hand, the estimates of the instrument error parameters for the like instruments (i.e. the gyroscopes if it was the gyroscope that failed) for the non-degraded navigation unit will also be significantly large (relative to nominal expectations). This occurs as the sensing axis directions for the gyroscopes (or accelerometers as the case may be) of the non-degraded navigation unit are significantly different in orientation from those of the gyroscopes (or accelerometers) of the degraded navigation unit, resulting in an assignment (estimate) of a degraded performance behavior to more than one instrument in the non-degraded navigation unit. Hence under the assumption that only a single gyroscope and/or accelerometer degradation will occur in one navigation unit at any one time, the unit with multiple instrument apparent degradation for instruments of that type will be assumed to be the non-degraded unit, so the degrading instrument is identified as the instrument in the other unit exhibiting error. With reference to Figure 4, Output vectors, X 1 , X 2 which include output signals from the inertial navigation systems (INS's) 72 and 74, are state vectors which may be expressed as follows: Where, X 1 is a set of states associated with INS 72 and X 2 is a set of states associated with INS 74; X T is the true or ideal state vector and e 1 and e 2 are the errors in the actual state vectors of INS 72 and 74. When output vectors X 1 and X 2 are joined at difference node 76, the true state vector, X T , drops out, so that the net output from node 76 is [ e 1 - e 2 ]. This difference quantity, [ e 1 - e 2 ], is then separately processed by two separate Kalman Filters 78 and 80, such that output error estimate vectors, ê 1 and ê 2 , [82, 84] are associated with respective Filters and respective, corresponding, INS. A significant extension of the state-of-the art for a redundant navigation system which is assumed to use 2 independent navigation units each comprising only 3 accelerometers and 3 gyroscopes is achieved. Customarily such a system would be termed "Fail-Safe" when the navigation solutions are compared as above, and they remain within a prescribed tolerance of each other; it is then concluded that both navigation units are properly operating and the navigation solutions are deemed reliable or "safe". On the other hand, if the comparison of the navigation solutions exceeds a prescribed tolerance, a fault or degradation would be declared and neither navigation solution would be assumed reliable as one could not determine which is obtained from the degraded navigation unit. Consequently an "Unsafe" situation now exists without the use of some other independent navigation systen. However, in this invention, since the degraded or failed accelerometer and/or gyroscope in one navigation unit is identified, the non-degraded navigation unit with its reliable navigation solution is identified. Consequently an improved situation to that described in the above paragraph has been realized without the use of some other independent navigation sensor. The described embodiment also includes a feature such that the property termed "Fail-Operate", "Fail-Safe" is realized. To obtain the latter stage of "Fail-Safe" with the situation of a degraded or failed gyroscope and/or accelerometer in one unit, additional navigation solutions must be obtained from the remaining non-degraded instruments such that a further failure or degradation of an accelerometer and/or gyroscope will be detected (isolation is not required) by comparison of these navigation solutions. This capability is obtained by combining the remaining non-degraded instruments in the degraded navigation unit with the individual gyroscopes and accelerometers of the non-degraded navigation unit, one at a time, so as to generate a set of 3 navigation solutions. For example if a degraded or failed gyroscope has been identified in one unit, the triad of accelerometers and 2 non-degraded gyroscopes in this unit can be employed with the 3 gyroscopes in the non-degraded unit one at a time to generate 3 distinct navigation solutions (note that ten distinct navigation solutions exist). Comparison of these solutions between themselves and with the navigation solution from the non-degraded unit provides the basis for detection of an additional instrument failure or degradation in either navigation unit. The practical difficulty with the above approach in obtaining accurate navigation solutions, using instruments in different navigation units, arises due to the existence of unknown static and dynamic misalignments between the two instrument assemblies (or blocks) of the 2 navigation units. The static and/or slowly-changing misalignments between the instrument blocks can be measured with high accuracy on a continual basis by comparison of the computed vehicle or body orientation as obtained from each of the navigation units, further enhanced via the processing of a Kalman estimator incorporating these misalignments as error states. Note further that the mounting misalignments of the gyroscopes and accelerometers relative to each other within each navigation unit, although a much less serious source of navigation error, are also continuously calibrated. The dynamic misalignments between the instrument blocks of the 2 navigation units are highly dependent on the interconnecting mechanical structure and the forces imposed upon it due to vehicle dynamics. When all the inertial instruments are operating properly, processed differential measurements (e.g. measured angular change and force differences and computed orientation differences) between the inertial instruments of the 2 navigation units yield precise indications of these dynamic misalignments (flexure) including amplitude, frequency, the relative phase and the extent of coherence of the motion about any 3 orthogonal axes. This information can be employed to construct predictive dynamic models of the differential dynamic flexure between the instrument blocks of the 2 navigation units. Hence for a reasonably well-behaved mechanical structure (i.e. a structure exhibiting some coherence between the differential angular motion about 3 orthogonal axes), such a predictive model can estimate the dynamic flexure motion in the absence of a full set of processed differential instrument measurements between the 2 navigation units. Consequently when a gyroscope and/or accelerometer in one navigation unit is identified as having faulty operation, then the predictive model of dynamic differential motion of the instrument blocks of the 2 navigation units can be employed to enable an improved utilization of instrument measurements obtained from one navigation unit with those from the other navigation unit to obtain an improved navigation solution. Clearly in the event that a faulty accelerometer is identified, full knowledge of the dynamic differential angular motion between the 2 instrument blocks is available from the properly operating gyroscope triads of each navigation unit. This permits utilization of accelerometer measurements from the non-degraded navigation unit with the 2 accelerometer measurements of the degraded navigation unit to obtain rather high-quality navigation solutions. Note further that the navigation solutions obtained by using the instruments from one inertial unit with those of the other navigation unit, enhanced by employing static and dynamic estimates of misalignments between the instrument blocks of the 2 inertial units, can be continuously computed and compared with the (most accurate) navigation solutions of each navigation unit. This comparison provides not only an indication of the quality of such a navigation solution but also serves as a basis for improving the estimates of the static misalignments and the predictive models for the dynamic misalignment. Figures 5A and 5B show a more detailed operation of the fault detection system. With reference to Figure 5A, it can be,seen that generally the Inertial Navigation Systems, INS 1 (101) and INS 2 (102) provide System Navigation outputs X out to the Aircraft or vehicle computer, which outputs may then be used for navigation. Additionally, the respective output state Vectors X 1 and X 2 may be combined at the Summer 103 to provide error signals which allow determination of which instruments of the dual INS installation are exhibiting degraded performance. The objective of the fault detection and isolation logic 100 of Figure 5A is to employ large differences of commensurate navigation outputs as computed parameters, such as position, velocity, and vehicle (or instrument frame) orientation between the two INS systems 101 and 102, for the purposes of: (1) detecting that a fault or faulty instrument exists; and (2) attributing this fault to the individual inertial instrument indicating the faulty operation so that this instrument may be isolated. Where fault isolation can be achieved and the fault is in only one of the navigation systems 101 or 102, then system fault tolerance is enhanced as the properly operating system is identified. An architecture for implementing a preferred embodiment of the fault tolerance system shown generally in Figure 5A is shown in Figure 5B. The Inertial Navigation Systems, INS 1 (101) and INS 2 (102) provide System Navigation outputs X out , to the Aircraft or vehicle computer, which outputs may then be used for navigation (as in Figure 5A). Additionally, the respective output Vectors 110 (X T + e 1 ) and 112 (X T + e 2 ) may be combined as follows (at nodes 111 and 113, respectively): Vector 110 with ê 1 , and Vector 112 with ê 2 . The resulting difference from such a combination provides an output of X T + along flow path 114 and an output of X T + along flow path 116 (where and are errors in the estimates ê 1 , ê 2 of the errors e 1 ,e 2 in individual INS's respectively) . The resulting differences 114 and 116 are then combined (at the summer node 115) to produce the result shown at flow path 120, namely  = - , where = [ e 1 - ê 1 ]; = [ e 2 - ê 2 ]: and,  = Observation. The vector, ê 1 , is known as the estimate of the error vector e 1 for INS 1 (101); and the vector ê 2 is known as the estimate of the error vector e 2 for INS 2 (102). The estimates, ê 1 , and ê 2 , are provided which allow determination of which instruments of the dual INS installation are exhibiting degraded performance. Here, certain error state variables (for position (P), velocity (V), and orientation (O)), set forth in the Navigational Co-ordinates, N (North), E (East), and V (Vertical), form the sub-vectors e s1 and e s2 : Only the sub-vectors, e s1 and e s2 , of the raw Observation,  = - , are processed through Kalman Filters 122 and 124 (gain elements) for deriving an input signal to the Open Loop Filter Estimate Propagators 126 and 128, which is used to estimate new values of ê 1 and ê 2 . Other error state variables, such as gyro drift, which are included in the vectors e 1 and e 2 , are not part of the sub-vectors, e s1 and e s2 , and are not processed by the Kalman Filters 122 and 124, nor are these values processed by the Propagators 126 and 128. Propagators 126 and 128 are optimal estimate propagators which act here, in an open loop fashion, to produce the optimum error estimate signals, ê 1 , and ê 2 . A detailed explanation of the operation of open loop optimal estimate propagators, such as propagators 126 and 128 (as well as gain elements 122 and 124), is disclosed in an article by J.R. Huddle (the applicant herein), entitled "Chapter 11 - APPLICATION OF KALMAN FILTERING THEORY TO AUGMENTED INERTIAL NAVIGATION SYSTEMS", at pages 231 - 268, and found in publication 139 of the Guidance and Control Panel of AGARD-NATO (North Atlantic Treaty Organization [NATO], Advisory Group for Aerospace Research and Development [AGARD]), entitled THEORY AND APPLICATION OF KALMAN FILTERING (1970). In particular, Figure 10 (page 262) of the article and its accompanying description (at pages 247 - 251 of the article) explain the operation of propagators like those at 126 and 128 of Figures 5B and 5C, acting in concert with gain elements 122 and 124, to provide an open loop Kalman Filter estimate. The outputs of propagators 126 and 128 are re-computed values of the error estimate vectors, ê 1 and ê 2 , which values are used to correct the error vector for each Navigational System. An alternate embodiment to the system shown in Figure 5B has a Fault Detection and Isolation Logic system which estimates error with respect to the Inertial Navigation Systems (INS) parameters, the error estimates associated with one of the Inertial Navigation Systems being isolated from the error estimates associated with the other system. As with the system of Figure 5B, the Inertial Navigation Systems, INS 1 (101) and INS 2 (102) provide System Navigation outputs X out to the Aircraft or vehicle computer, which outputs may then be used for navigation (as in Figure 5A). Additionally, the respective output Vectors (X + e 1 ) and (X + e 2 ) may be combined at a node, resulting in an output along a flow path of a raw observation  computed according to the equation  = e 1 - e 2 . This observation is then corrected by the relevant error estimate state variables (of position, velocity, and orientation) found in the sub-vectors, e s1 and e s2 , and only these sub-vectors are processed in the Kalman filters (122 and 124). The outputs of the Kalman filters (122 and 124) are then processed by respective Propagators (126 and 128). The error signals, and are then processed through the Kalman Filters 122 and 124 (which compute gain elements) for deriving an input signal to the Open Loop Error Filter Estimate Propagators (126 and 128). As in Figure 5B, the Propagators (126 and 128) are optimal estimate propagators which act, in an open loop fashion, to provide optimum error estimates, ê 1 and ê 2 of the error vectors e 1 and e 2 , respectively, in the system. It can be seen that in this embodiment the resulting error vectors, ê 1 an ê 2 are computed without being affected by the computation of each other. This is in contra-distinction to the embodiment in Figure 5B wherein such an effect of ê 1 on ê 2 and ê 2 on ê 1 is present. While preferred embodiments are described, it is clear that alternative equivalent embodiments of the invention may be envisioned which provide adequate alternatives, performing similar functions to the preferred embodiment, yet using the basic teachings and principles of the herein described invention. For example, although the invention is primarily directed at fault tolerant Navigation systems, the principles which govern such Systems also may be applied to Flight Control Systems to detect Fail-Operate, Fail-Safe conditions. It is also possible to utilise a least squares algorithm instead of Kalman Filters to perform optimal estimation functions in the above embodiments.

Claims: A fault-tolerant inertial navigation system (70) comprising two independent inertial navigation units, each of said inertial navigation units (101, 102) being fully capable of performing navigational functions and each of said inertial navigation units comprising a plurality of navigational instruments of two types, including three linear force sensors (38) and three angular change sensors (32, 34, 36), characterised in that the two said navigational units have no two linear sensors nor two angular change sensors of either unit co-linear or co-planar, said inertial navigation units being operable to produce respective sets of independent navigational solutions (X 1 , X 2 ) at their respective outputs, there being optimal estimation means (100) for comparing said independent navigational solutions of each of said navigation units by processing differences in the solutions, the optimal estimation producing, for each unit, a respective error estimate vector comprising the errors in the navigational variables, such as position, velocity and orientation, and also the instrument errors, and means for detecting any significantly degraded performance of any one sensor of either type by detecting in the associated error estimate vectors a degradation of a single instrument of a given instrument type in a first navigation unit and at the same time a degradation of multiple instruments of that same instrument type in the second navigation unit, the detecting means being adapted to isolate the single instrument in the first navigation unit indicating such degraded performance having identified it as being faulty. A fault-tolerant inertial navigation system according to claim 1, wherein said means (100) for comparing said independent navigational solutions includes a least squares estimation optimal algorithm. A fault-tolerant inertial navigation system according to claim 2 wherein said means (100) for comparing said independent navigational solutions includes an optimal estimation Kalman filter (78, 80) operating according to a Kalman algorithm. A fault-tolerant inertial navigation system according to claim 2 or 3, wherein the state errors for the instrument errors include factors such as individual biases of the angular change sensors and linear force sensors, scale factor errors, mounting misalignments of said angular change and linear force sensors within each of said navigation units with respect to each other, and mechanical misalignments between the two navigation units. A fault-tolerant inertial navigation system according to any one of the preceding claims whererein said means (100) for comparing said independent navigational solutions includes: means (126, 128) for computing a set of error estimate values from sub-vectors ê s1 and ê s2 of the error estimate vectors ê 1 and ê 2 , which sub-vectors are of error estimate values for computed navigation variables such as position, velocity and orientation; means (111, 113) for combining said set of said independent navigational solutions, which solutions are provided at each of the respective outputs of said inertial navigation units (101, 102), with corresponding ones of said computed error state estimate values; means for determining corrections in said error state estimate values as a function of the error in the estimated values of the independent navigational solutions from both of said inertial navigation units; and means for updating said error state estimate values with said corrections whereby estimated navigational solutions approach the true navigational solutions for each navigational unit so that fault detection of navigational instruments may be achieved. A fault-tolerant inertial navigation system according to any one of claims 1 to 4, wherein said means for comparing said independent navigational solutions includes: means for computing two sets of error estimate values, respective sets comprising estimates associated with error state variables, such as errors in position, velocity and orientation, for each of said navigational units; means for determining corrections in said error estimate values, wherein a function of the error estimates for each of said inertial navigation units is obtained without having an effect on the other separately; and means for updating said error estimate values with said corrections whereby estimated navigational solutions approach the true navigational solutions for each navigational unit so that fault detection of navigational instruments may be achieved.

Inventors: HUDDLE JAMES R, HUDDLE, JAMES R.
Applicants: LITTON SYSTEMS INC, LITTON SYSTEMS, INC.
Application year: 1992
Main classification: G01C21
IPC codes: G01C25, G01C21