Thesis - Leigh Moody.pdf - Bad Request - Cranfield University

More documents

Recommendations

Info

Chapter 4 / Target Tracking _ _ 4.12 Discussion Multiple-model (MM) filters are generally accepted as being more robust delivering substantially better performance than do single fixed or variable gain filters against manoeuvring targets. The early algorithms selected the best individual filter from a bank of filters. Later, more advanced algorithms combined the output from a bank of active filters according to the likelihood that they represent the true target dynamics. The IMM which is notable for its re-initialisation of filters in the filter bank, does not require a manoeuvre detector, and was selected for its simplicity and a performance that is equivalent to Bayesian filters with 2 hypothesis levels, Blom [B.9] . The tracking simulator hosts a conventional IMM whose filters are stimulated by reference or corrupted radar measurements and can be used either in isolation, or in combination. The IMM track is up-linked with missile plots, data time stamps and the updated IMM modal probabilities to the missile central processor. Here the tracks and plots are fused with IMU and seeker measurements to provide optimal data for missile guidance and stabilisation. Filters are provided for the most commonly encountered target motions, i.e. constant velocity, constant acceleration, high “g” turning (dog-leg) and weaves. As targets tend to manoeuvre for limited periods time, typically up to 5 s, earth referenced Cartesian position, velocity and acceleration states were selected rather than polar, or radar sight-line alternatives. For short-range tracking of agile targets it is better to retain the cross correlation that exists between the separated axes. A conventional EKF formulation was selected, even though for IMM application the tight control of system noise is paramount for discrimination purposes. A 10 Hz filter update rate was used for CLOS guidance, which is still high considering modern multi-purpose radar workloads. At this rate measurement 4-26 TARGET TRACKING SIMULATOR Read in user target tracking control data Read in user target tracking characterisation data I_IMM Compute tracking parameters TARGET SIMULATOR SENSOR SIMULATOR IMM_CONTROL IMM_MIXING ( 10 Hz ) Tracking filters and filter weight updates at 10Hz ( VEL_FILTER ) ( ACC_FILTER ) ( MK1_FILTER ) ( MK2_FILTER ) IMM Output / filter merging at 10Hz ( IMM_OUTPUT ) Target observer kinematics ( FF_TG_GEOMETRY ) Filter covariance monitoring ( CV_CONTROL ) ( CV_STATS ) Figure 4-7 : Target Tracking Simulator
Chapter 5 / Missile State Observer _ _ linearisation is rarely a problem. Filters that accurately propagate the state error probability density in high dynamic environments using Monte-Carlo methods such as Bootstrapping are considered too expensive at this stage. These type of filters will probably supplant the simpler algorithms used in this study as computer power increases. Filter initialisation using least-squares and α−β−γ filtering favoured the latter which did not introduce biases in a dynamic situation. The settling time for a 0.4 Hz bandwidth filter was typically 2-3 s. Probably the best approach for IMM initialisation is to set the acceleration filter probability to 1, and prevent transition to any other filter. Once settled the transitional probabilities can be restored. Transition between filters as the target changes its flight regime requires a filter with manoeuvre dynamics that inflates the state uncertainty. Direct jumps between the filters, without introducing Singer filter, are prohibited so as to inflate the covariance levels during transients. It is noted from literature that IMM performance is superior after a flight regime change compared with other filters. The IMM serially processes the radar measurements to improve EKF conditioning. This formulation also accommodates reduced measurement sets, as range-rate data is not always available. Range-rate is often unavailable due to ambiguities linked to geometrical restrictions. The formulation here provides the weighted state and covariance at the measurement reference time prior to any update. This is so that track fusion can be performed using the new information introduced to the IMM avoiding the destabilising effect of correlation at high data rates. The tuning and performance of the individual tracking filters using radar measurements corrupted by Gaussian noise is covered in §9. Consider now some extensions to the current work: • At high update rates the benefit of more robust EKF algorithms, and measurements processing order are irrelevant. In multiple target and missile engagements high update rates are often unsustainable. These are precisely the conditions in which poor linearisation of the EKF, and its underlying Gaussian tenants are violated, causing it to diverge. The stability of IMM tracking filters should be assessed for stability at 0.5 Hz and 1 Hz, repeating the filter tuning study presented in §9. • If linearisation causes filter divergence the iterated EKF should be tried with the emphasis on the number of iterations required. Second order filters are probably too expensive as an alternative. • Implement Li’s robust IMM formulation that avoids bounding the filter transition probabilities and assess its performance. Results published so far are inconclusive and do not warrant the processing load increase. • Investigate IMM filter re-initialisation rates for typical target manoeuvres. 4-27
Page 1:
CRANFIELD UNIVERSITY LEIGH MOODY SE
Page 5:
ABSTRACT When considering advances
Page 9 and 10:
Contents _ _ LIST OF CONTENTS 1 INT
Page 11 and 12:
Contents _ _ 8.2 The Scope of Moder
Page 13 and 14:
Contents _ _ 17.4 Inertial Velocity
Page 15 and 16:
Tables _ _ LIST OF TABLES Table 1-1
Page 17 and 18:
Figures _ _ LIST OF FIGURES Figure
Page 19 and 20:
Figures _ _ Figure 5-1 : Centralise
Page 21 and 22:
Figures _ _ Figure 19-3 : Air Densi
Page 23 and 24:
Acronyms _ _ Acronyms And Abbreviat
Page 25 and 26:
Acronyms _ _ HDOP - NAVSTAR GPS Hor
Page 27 and 28:
Acronyms _ _ RCS - Radar Cross Sect
Page 29 and 30:
Glossary _ _ GLOSSARY A challenge w
Page 31 and 32:
Glossary _ _ 0.1 Predicate Calculus
Page 33 and 34:
Glossary _ _ ]A,B] Real number rang
Page 35 and 36:
Glossary _ _ 0.9 Matrix Operators [
Page 37 and 38:
Glossary _ _ 0.14.2 Special Vectors
Page 39 and 40:
Glossary _ _ P C a , b ≡ XC YC ZC
Page 41 and 42:
Glossary _ _ V ≡ V : = V • V Th
Page 43 and 44:
Glossary _ _ 0.16.4 Matrix Partitio
Page 45 and 46:
Glossary _ _ Only the subset of qua
Page 47 and 48:
Glossary _ _ 0.19 Systeme Internati
Page 49 and 50:
1 Chapter 1 / Introduction _ _ Chap
Page 51 and 52:
Chapter 1 / Introduction _ _ Wherea
Page 53 and 54:
Chapter 1 / Introduction _ _ • Cr
Page 55 and 56:
Chapter 1 / Introduction _ _ genera
Page 57 and 58:
Chapter 1 / Introduction _ _ radar
Page 59 and 60:
Chapter 1 / Introduction _ _ simple
Page 61 and 62:
Chapter 1 / Introduction _ _ optimi
Page 63 and 64:
Chapter 1 / Introduction _ _ 1.3.9
Page 65 and 66:
2 Chapter 2 / Target Modelling _ _
Page 67 and 68:
Chapter 2 / Target Modelling _ _ 2.
Page 69 and 70:
Chapter 2 / Target Modelling _ _
Page 71 and 72:
Chapter 2 / Target Modelling _ _ t
Page 73 and 74:
Chapter 2 / Target Modelling _ _ P&
Page 75 and 76:
Chapter 2 / Target Modelling _ _ GO
Page 77 and 78:
Chapter 2 / Target Modelling _ _ th
Page 79 and 80:
Chapter 2 / Target Modelling _ _
Page 81 and 82:
Chapter 2 / Target Modelling _ _ VX
Page 83 and 84:
Chapter 2 / Target Modelling _ _ ma
Page 85 and 86:
3 Chapter 3 / Sensors _ _ Chapter 3
Page 87 and 88:
Chapter 3 / Sensors _ _ 3.1 Simulat
Page 89 and 90:
Chapter 3 / Sensors _ _ Table 3-4 :
Page 91 and 92:
Chapter 3 / Sensors _ _ Reference D
Page 93 and 94:
Chapter 3 / Sensors _ _ 3.2-9 s s i
Page 95 and 96:
Chapter 3 / Sensors _ _ 3.2-11 t o
Page 97 and 98:
Chapter 3 / Sensors _ _ Figure 3-5
Page 99 and 100:
Chapter 3 / Sensors _ _ Table 3-7 :
Page 101 and 102:
Chapter 3 / Sensors _ _ IF ϕ LIM
Page 103 and 104:
Chapter 3 / Sensors _ _ The phase e
Page 105 and 106:
Chapter 3 / Sensors _ _ Taking expe
Page 107 and 108:
Chapter 3 / Sensors _ _ Expressing
Page 109 and 110:
Chapter 3 / Sensors _ _ INPUT; AA,
Page 111 and 112:
Chapter 3 / Sensors _ _ The functio
Page 113 and 114:
Chapter 3 / Inertial Navigation _ _
Page 115 and 116:
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Chapter 3 / Sensors / Gyroscopes _
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
Page 131 and 132:
Page 133 and 134:
Page 135 and 136:
Page 137 and 138:
Chapter 3 / Sensors / Accelerometer
Page 139 and 140:
Page 141 and 142:
Page 143 and 144:
Page 145 and 146:
Page 147 and 148:
Chapter 3 / Sensors / Barometric Al
Page 149 and 150:
Chapter 3 / Sensors / Barometric Al
Page 151 and 152:
Chapter 3 / Sensors / Radar Altimet
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Chapter 3 / Sensors / Radar _ _ 3.8
Page 159 and 160:
Chapter 3 / Sensors / Radar _ _ LF
Page 161 and 162:
Chapter 3 / Sensors / Radar _ _ ( )
Page 163 and 164:
Page 165 and 166:
Chapter 3 / Sensors / Radar _ _ S :
Page 167 and 168:
Chapter 3 / Sensors / Radar _ _ SN
Page 169 and 170:
Page 171 and 172:
Chapter 3 / Sensors / Radar _ _ 2
Page 173 and 174:
Chapter 3 / Sensors / Radar _ _ ⎛
Page 175 and 176:
Chapter 3 / Sensors / Seeker _ _ 3.
Page 177 and 178:
Chapter 3 / Sensors / Seeker _ _ 5
Page 179 and 180:
Page 181 and 182:
Chapter 3 / Sensors / Seeker _ _
Page 183 and 184:
Chapter 3 / Sensors / Seeker _ _ th
Page 185 and 186:
Chapter 3 / Sensors / Seeker _ _ Th
Page 187 and 188:
Page 189 and 190:
Chapter 3 / Sensors / Seeker _ _ Th
Page 191 and 192:
Page 193 and 194:
Chapter 3 / Sensors / Fins _ _ 3.10
Page 195 and 196:
Chapter 3 / Sensors / Fins _ _ thro
Page 197 and 198:
Chapter 3 / Sensors / NAVSTAR GPS _
Page 199 and 200:
Page 201 and 202:
Page 203 and 204:
Page 205 and 206:
Page 207 and 208: Chapter 3 / Sensors / NAVSTAR GPS _
Page 217 and 218: Chapter 3 / Sensors / Helmet Mounte
Page 219 and 220: Chapter 3 / Sensors / Helmet Mounte
Page 221 and 222: Chapter 3 / Sensors / Air Data Syst
Page 227 and 228: Chapter 4 / Target Tracking _ _ 3.1
Page 229 and 230: Chapter 4 / Target Tracking _ _ Ine
Page 231 and 232: Chapter 4 / Target Tracking _ _ ran
Page 233 and 234: Chapter 5 / Missile State Observer
Page 257: Chapter 5 / Missile State Observer
Page 261 and 262: 5 Chapter 5 / Missile State Observe
Page 295 and 296: 6 Chapter 6 / Missile Guidance _ _
Page 297 and 298: Chapter 6 / Missile Guidance _ _ 6.
Page 299 and 300: Chapter 6 / Missile Guidance _ _ As
Page 301 and 302: Chapter 6 / Missile Guidance _ _
Page 303 and 304: Chapter 6 / Missile Guidance _ _ CD
Page 305 and 306: Chapter 6 / Missile Guidance _ _ ge
Page 307 and 308: Chapter 6 / Missile Guidance _ _ ex
Page 309 and 310:
Chapter 6 / Missile Guidance _ _ &
Page 311 and 312:
Chapter 6 / Missile Guidance _ _ PN
Page 313 and 314:
Chapter 6 / Missile Guidance _ _ ra
Page 315 and 316:
Chapter 6 / Missile Guidance _ _ of
Page 317 and 318:
Chapter 6 / Missile Guidance _ _ NO
Page 319 and 320:
Chapter 6 / Missile Guidance _ _ 6.
Page 321 and 322:
Chapter 6 / Missile Guidance _ _ tr
Page 323 and 324:
Chapter 6 / Missile Guidance _ _ η
Page 325 and 326:
Page 327 and 328:
Chapter 6 / Missile Guidance _ _ Au
Page 329 and 330:
Page 331 and 332:
Chapter 6 / Missile Guidance _ _ Fo
Page 333 and 334:
Chapter 6 / Missile Guidance _ _ (
Page 335 and 336:
Chapter 6 / Missile Guidance _ _
Page 337 and 338:
Chapter 6 / Missile Guidance _ _ ar
Page 339 and 340:
7 Chapter 7 / Missile Trajectory Op
Page 341 and 342:
Chapter 7 / Missile Trajectory Opti
Page 343 and 344:
Page 345 and 346:
Page 347 and 348:
Page 349 and 350:
Page 351 and 352:
Page 353 and 354:
Page 355 and 356:
Page 357 and 358:
Page 359 and 360:
Page 361 and 362:
8 Chapter 8 / Simulation _ _ Chapte
Page 363 and 364:
Chapter 8 / Simulation _ _ 8.1 The
Page 365 and 366:
Chapter 8 / Simulation _ _ 8.3 The
Page 367 and 368:
Chapter 8 / Simulation _ _ Having p
Page 369 and 370:
Chapter 8 / Simulation _ _ 8.5.1 Gl
Page 371 and 372:
Chapter 8 / Simulation _ _ (1) CONS
Page 373 and 374:
Chapter 8 / Simulation _ _ 8.6.2 Ou
Page 375 and 376:
Chapter 8 / Simulation _ _ The file
Page 377 and 378:
Chapter 8 / Simulation _ _ • The
Page 379 and 380:
Chapter 8 / Simulation _ _ comprehe
Page 381 and 382:
Chapter 8 / Simulation _ _ WIN_RATE
Page 383 and 384:
Chapter 8 / Simulation _ _ for this
Page 385 and 386:
Chapter 8 / Simulation _ _ with the
Page 387 and 388:
Chapter 8 / Simulation _ _ Figure 8
Page 389 and 390:
Chapter 8 / Simulation _ _ Table 8-
Page 391 and 392:
Chapter 8 / Simulation _ _ 8.8 Disc
Page 393 and 394:
9 Chapter 9 / Performance _ _ Chapt
Page 395 and 396:
Chapter 9 / Performance _ _ 9.1 Air
Page 397 and 398:
Chapter 9 / Performance _ _ XM ( >
Page 399 and 400:
Chapter 9 / Performance _ _ 9.3 PN
Page 401 and 402:
Chapter 9 / Performance _ _ The eff
Page 403 and 404:
Chapter 9 / Performance _ _ VXMVOM
Page 405 and 406:
Chapter 9 / Performance _ _ VXMVOM
Page 407 and 408:
Chapter 9 / Performance _ _ 9.4 CLO
Page 409 and 410:
Chapter 9 / Performance _ _ AR_BOM
Page 411 and 412:
Chapter 9 / Performance Chapter 9 /
Page 413 and 414:
Initially the position error falls
Page 415 and 416:
values of CN are not always a relia
Page 417 and 418:
crude initialisation introduces err
Page 419 and 420:
9.5.3 Singer Filter Tuning The Sing
Page 421:
9.6.2 CLOS Study The CLOS study sho
Page 424 and 425:
Chapter 10 / Conclusions _ _ 10-2
Page 426 and 427:
Chapter 10 / Conclusions _ _ 10.3 T
Page 428 and 429:
Chapter 10 / Conclusions _ _ 10.7 M
Page 430 and 431:
Chapter 11 / Future Research _ _ 11
Page 432 and 433:
Chapter 11 / Future Research _ _
Page 434 and 435:
Chapter 11 / Future Research _ _ To
Page 436 and 437:
References _ _ B.4 BAZARAA M.S., SH
Page 438 and 439:
References _ _ F.1 FOX J.E., “A C
Page 440 and 441:
References _ _ H.5 #HULL D.G., RADK
Page 442 and 443:
References _ _ L.2 LOOZE D.P., HSU
Page 444 and 445:
References _ _ N.4 NABAA N., BISHOP
Page 446 and 447:
References _ _ R.3 RUSNACK I., “O
Page 448 and 449:
References _ _ S.15 SINGER R.A.,
Page 450 and 451:
References _ _ Y.2 YUAN P., CHERN J
Page 452 and 453:
Bibliography _ _ B.13 BABA Y., YAMA
Page 454 and 455:
Bibliography _ _ B.40 BECKER J.C.,
Page 456 and 457:
Bibliography _ _ C.33 CORTINA E., O
Page 458 and 459:
Bibliography _ _ E.8 ERSHOV A.A.,
Page 460 and 461:
Bibliography _ _ G.34 GUTMAN P., VE
Page 462 and 463:
Bibliography _ _ H.35 HUSSAIN A.M.,
Page 464 and 465:
Bibliography _ _ K.14 KATZIR S., CL
Page 466 and 467:
Bibliography _ _ L.19 LEFAS C.C,
Page 468 and 469:
Bibliography _ _ M.16 MAYNE D.Q., P
Page 470 and 471:
Bibliography _ _ P.1 PAINTER J.H.,
Page 472 and 473:
Bibliography _ _ R.32 RONG LI X., Z
Page 474 and 475:
Bibliography _ _ S.47 SPEYER J.L.,
Page 476 and 477:
Bibliography _ _ V.5 VIAN J.L., MOO
Page 478 and 479:
Bibliography _ _ W.29 WATSON G.A.,
Page 480 and 481:
Appendix A / Geometric Points _ _ 1
Page 482 and 483:
Appendix A / Geometric Points _ _ 1
Page 484 and 485:
Appendix B / Frames of Reference _
Page 486 and 487:
Page 488 and 489:
Page 490 and 491:
Page 492 and 493:
Page 494 and 495:
Appendix C / Axis Transforms _ _ 16
Page 496 and 497:
Appendix C / Axis Transforms _ _ YP
Page 498 and 499:
Appendix C / Axis Transforms _ _ B
Page 500 and 501:
Appendix C / Axis Transforms _ _ YB
Page 502 and 503:
Page 504 and 505:
Appendix C / Axis Transforms _ _ Us
Page 506 and 507:
Appendix C / Axis Transforms _ _ No
Page 508 and 509:
Appendix C / Axis Transforms _ _ B
Page 510 and 511:
Appendix C / Axis Transforms _ _
Page 512 and 513:
Page 514 and 515:
Appendix D / Point Mass Dynamics _
Page 516 and 517:
Page 518 and 519:
Page 520 and 521:
Page 522 and 523:
Page 524 and 525:
Page 526 and 527:
Appendix E / Earth Geometry _ _ 18-
Page 528 and 529:
Appendix E / Earth Geometry _ _ ELL
Page 530 and 531:
Appendix E / Earth Geometry _ _ (dx
Page 532 and 533:
Appendix E / Earth Geometry _ _ Int
Page 534 and 535:
Appendix E / Earth Geometry _ _ 18.
Page 536 and 537:
Appendix E / Earth Geometry _ _ 19-
Page 538 and 539:
Appendix E / Earth Geometry _ _ P S
Page 540 and 541:
Appendix E / Earth Geometry _ _ 19.
Page 542 and 543:
Appendix E / Earth Geometry _ _ ∂
Page 544 and 545:
Appendix G / Gravity _ _ 20-2
Page 546 and 547:
Appendix G / Gravity _ _ g : = g +
Page 548 and 549:
Appendix G / Gravity _ _ d −6 2
Page 550 and 551:
Appendix G / Gravity _ _ 20-8
Page 552 and 553:
Appendix H / Steady State Tracking
Page 554 and 555:
Page 556 and 557:
Page 558 and 559:
Page 560 and 561:
Page 562 and 563:
Appendix I / Utilities _ _ 22.1-2
Page 564 and 565:
Appendix I / Utilities _ _ Cartesia
Page 566 and 567:
Appendix I / Utilities _ _ Matrix P
Page 568 and 569:
Appendix I / Utilities _ _ 22.1-8
Page 570 and 571:
Appendix I / Utilities / General Ut
Page 572 and 573:
Page 574 and 575:
Page 576 and 577:
Page 578 and 579:
Page 580 and 581:
Page 582 and 583:
Page 584 and 585:
Appendix I / Utilities / WGS 84 Tar
Page 586 and 587:
Page 588 and 589:
Page 590 and 591:
Page 592 and 593:
Page 594 and 595:
Page 596 and 597:
Appendix I / Utilities / Axis Trans
Page 598 and 599:
Page 600 and 601:
Page 602 and 603:
Page 604 and 605:
Page 606 and 607:
Page 608 and 609:
Page 610 and 611:
Page 612 and 613:
Appendix I / Utilities / Point Mass
Page 614 and 615:
Page 616 and 617:
Page 618 and 619:
Page 620 and 621:
Page 622 and 623:
Appendix I / Utilities / Earth, Atm
Page 624 and 625:
Appendix I / Utilities / Earth, Atm
Page 626 and 627:
Appendix I / Utilities / Digital Ma
Page 628 and 629:
Appendix I / Utilities / Digital Fi
Page 630 and 631:
Page 632 and 633:
Page 634 and 635:
Page 636 and 637:
Page 638 and 639:
Page 640 and 641:
Page 642 and 643:
Page 644 and 645:
Appendix I / Utilities / Matrices _
Page 646 and 647:
Page 648 and 649:
Page 650 and 651:
Page 652 and 653:
Appendix I / Utilities / Quaternion
Page 654 and 655:
Page 656 and 657:
Page 658 and 659:
Page 660 and 661:
Page 662 and 663:
Page 664 and 665:
Appendix I / Utilities / Trigonomet
Page 666 and 667:
Page 668 and 669:
Page 670 and 671:
Appendix I / Utilities / Vectors _
Page 672 and 673:
Page 674 and 675:
Page 676 and 677:
Appendix I / Utilities / Covariance
Page 678 and 679:
Page 680 and 681:
Page 682 and 683:
Page 684 and 685:
Page 686 and 687:
Page 688 and 689:
Page 690:
show all

Thesis - Leigh Moody.pdf - Bad Request - Cranfield University

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?