| 313 | | |
| 314 | | == Range offset calibration == |
| 315 | | |
| 316 | | Range offset correction (+range card calibration) is to correct for the slightly different timing of the 4 range cards (R1-R4) in both banks (A & B) in the system, and to correct any overall ground offset. |
| 317 | | |
| 318 | | Two datasets are required: |
| 319 | | 1. A real dataset with: |
| 320 | | 1. a source of multiple returns, such a forest (for step 1 below) |
| 321 | | 1. a strip with well known distances (for verification) |
| 322 | | 1. BIT (Built-In Test) mode data, where the range cards are all electronically fed with identical fake data representing the same distance. All cards should give the same result, so differences are used to calibrate each card against the others. |
| 323 | | |
| 324 | | First, we need to determine the timing differences between the 4 range cards (R1-R4) in each bank. To do this, we use a dataset with multiple varying returns present - we need combinations of 2-4 returns (forests are good for this, being tall and porous enough to give multiple returns). When there are less than 4 returns, R4 is a second measurement (not a copy of) of the last pulse - i.e. if there are 2 returns, you will have R1, R2 and R4 (= re-measurement of R2). This is exploited to compute the difference in timing between R2 and R4 (averaging many 2-returns). Similary 1-return and 3-return pulses are used to measure R1-R4 and R3-R4 differences. The end result is a set of timing differences between all the cards in a bank. |
| 325 | | |
| 326 | | Second, we need to establish the timing differences between bank A and bank B. As with the first step, we need the timing cards to measure exactly the same instant. To do this, we use BIT mode data, where R1 in both bank receives the same electronically generated pulse at the same instant and are thus measuring the same event. Averaging these numbers gives the timing offsets between the R1 cards, which can be combined with the first measurements to establish timing between all cards. |
| 327 | | |
| 328 | | ''PROCEDURE:'' |
| 329 | | |
| 330 | | Can do range correction if the boresight results are good. This is a 2 stage process: |
| 331 | | |
| 332 | | * 1. Nominal offset determination A1 |
| 333 | | * 2. Define relative differences for A2,A3,A4 and B1,B2,B3,B4 |
| 334 | | |
| 335 | | points have approx. the same range error within +/-7 degrees of Nadir, so we look only at this region firstly. |
| 336 | | |
| 337 | | * In ALSPP filters dialog set the angles to +7 and -7 degrees, change the output directory (to 02a_Roff+-7deg if using suggested directory structure) and run the processing on the 4 low altitude flight lines. |
| 338 | | * Load the results into TerraScan and use the 30-40 GCPs of the calibration site. |
| 339 | | * Tools -> Output Control Report |
| 340 | | * Browse -> GCP file and remove bad points (maybe an error occurred in the surveying of a certain point) |
| 341 | | * Look at the dz value, the average dz is used for the nominal range offset A1. |
| 342 | | * Save the text file. |
| 343 | | |
| 344 | | Preferably using data including areas of forest and the BIT mode data, run RangeCardCal (from ALSPP tools menu) and enter the average dz value as A1 to get the other offsets. Add the outputs to the ALSPP dialog and save the settings reg file (to a new name) |
| 345 | | |
| 346 | | To check these results re-run using the full FOV (~45 degrees) and check average dz is less than 1cm or so, and standard deviation <5cm in TerraScan control report. (also look at cross sections) |
| 347 | | |
| 348 | | Then process the 4 high altitude flights in ALSPP and check in TerraScan (around nadir and swath edges) |
| 349 | | |
| 350 | | Finally load in all flights into TerraScan (within a fence if memory issues) and check them (ideally along a stream because this has a “good” profile) Can use the travel path tool in TerraScan for comparing cross sections along a path. |
| | 462 | == Range offset calibration == |
| | 463 | |
| | 464 | Range offset correction (+range card calibration) is to correct for the slightly different timing of the 4 range cards (R1-R4) in both banks (A & B) in the system, and to correct any overall ground offset. |
| | 465 | |
| | 466 | Two datasets are required: |
| | 467 | 1. A real dataset with: |
| | 468 | 1. a source of multiple returns, such a forest (for step 1 below) |
| | 469 | 1. a strip with well known distances (for verification) |
| | 470 | 1. BIT (Built-In Test) mode data, where the range cards are all electronically fed with identical fake data representing the same distance. All cards should give the same result, so differences are used to calibrate each card against the others. |
| | 471 | |
| | 472 | First, we need to determine the timing differences between the 4 range cards (R1-R4) in each bank. To do this, we use a dataset with multiple varying returns present - we need combinations of 2-4 returns (forests are good for this, being tall and porous enough to give multiple returns). When there are less than 4 returns, R4 is a second measurement (not a copy of) of the last pulse - i.e. if there are 2 returns, you will have R1, R2 and R4 (= re-measurement of R2). This is exploited to compute the difference in timing between R2 and R4 (averaging many 2-returns). Similary 1-return and 3-return pulses are used to measure R1-R4 and R3-R4 differences. The end result is a set of timing differences between all the cards in a bank. |
| | 473 | |
| | 474 | Second, we need to establish the timing differences between bank A and bank B. As with the first step, we need the timing cards to measure exactly the same instant. To do this, we use BIT mode data, where R1 in both bank receives the same electronically generated pulse at the same instant and are thus measuring the same event. Averaging these numbers gives the timing offsets between the R1 cards, which can be combined with the first measurements to establish timing between all cards. |
| | 475 | |
| | 476 | ''PROCEDURE:'' |
| | 477 | |
| | 478 | Can do range correction if the boresight results are good. This is a 2 stage process: |
| | 479 | |
| | 480 | * 1. Nominal offset determination A1 |
| | 481 | * 2. Define relative differences for A2,A3,A4 and B1,B2,B3,B4 |
| | 482 | |
| | 483 | points have approx. the same range error within +/-7 degrees of Nadir, so we look only at this region firstly. |
| | 484 | |
| | 485 | * In ALSPP filters dialog set the angles to +7 and -7 degrees, change the output directory (to 02a_Roff+-7deg if using suggested directory structure) and run the processing on the 4 low altitude flight lines. |
| | 486 | * Load the results into TerraScan and use the 30-40 GCPs of the calibration site. |
| | 487 | * Tools -> Output Control Report |
| | 488 | * Browse -> GCP file and remove bad points (maybe an error occurred in the surveying of a certain point) |
| | 489 | * Look at the dz value, the average dz is used for the nominal range offset A1. |
| | 490 | * Save the text file. |
| | 491 | |
| | 492 | Preferably using data including areas of forest and the BIT mode data, run RangeCardCal (from ALSPP tools menu) and enter the average dz value as A1 to get the other offsets. Add the outputs to the ALSPP dialog and save the settings reg file (to a new name) |
| | 493 | |
| | 494 | To check these results re-run using the full FOV (~45 degrees) and check average dz is less than 1cm or so, and standard deviation <5cm in TerraScan control report. (also look at cross sections) |
| | 495 | |
| | 496 | Then process the 4 high altitude flights in ALSPP and check in TerraScan (around nadir and swath edges) |
| | 497 | |
| | 498 | Finally load in all flights into TerraScan (within a fence if memory issues) and check them (ideally along a stream because this has a “good” profile) Can use the travel path tool in TerraScan for comparing cross sections along a path. |
| | 499 | |
| | 500 | |