Collision probability computation for conjunction assessment
Split ocaml-transport into ocaml-cltu and ocaml-cop1
- ocaml-cltu: CLTU encoding/decoding (CCSDS 231.0-B) with BCH(63,56),
ASM sync markers (131.0-B), and stream sync parsers
- ocaml-cop1: COP-1 state machines (CCSDS 232.1-B) for FOP-1 (ground)
and FARM-1 (flight) with Eio service layer
- cltu-eio: CLTU/ASM send/recv over Eio flows
- cop1-eio: COP-1 service layer with Eio timer management
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test/interop/gmat/test.ml
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test/interop/gmat/test.ml
···
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(** GMAT interop tests for ocaml-collision.
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Uses two-object OEM traces from GMAT R2026a to compute miss distances and
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validate conjunction geometry.
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Uses two-object OEM traces from GMAT R2026a to validate conjunction
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geometry. Tests both plumbing (can we parse the data) and mission-ready
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properties (is our TCA/miss distance accurate enough for CA decisions).
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Source: GMAT R2026a, conjunction_leo.script. *)
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···
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min_dist := d;
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min_epoch := sv1.(i).epoch)
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done;
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(* Two objects on crossing orbits should have closest approach *)
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Alcotest.(check bool) "min distance found" true (Float.is_finite !min_dist);
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Alcotest.(check bool) "min distance < 1000 km" true (!min_dist < 1000.0);
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(* Should not collide (different orbital planes cross at two points,
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but the satellites are unlikely to be at the crossing point simultaneously) *)
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Alcotest.(check bool) "no collision (> 1 km)" true (!min_dist > 1.0);
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Printf.printf " Closest approach: %.3f km at %s\n" !min_dist !min_epoch
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Printf.printf " Step-based closest approach: %.3f km at %s\n" !min_dist
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!min_epoch
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let test_relative_velocity () =
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let oem1 = parse_oem "conjunction_sat1.oem" in
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let oem2 = parse_oem "conjunction_sat2.oem" in
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let sv1 = Odm.state_vectors (List.hd (Odm.segments oem1)) in
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let sv2 = Odm.state_vectors (List.hd (Odm.segments oem2)) in
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(* At closest approach, relative velocity should be high (crossing orbits) *)
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let n = min (Array.length sv1) (Array.length sv2) in
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let min_i = ref 0 in
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let min_dist = ref Float.infinity in
···
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Alcotest.(check bool) "high relative velocity" true (dv > 5.0);
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Printf.printf " Relative velocity at TCA: %.3f km/s\n" dv
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(* MISSION-READY TEST: TCA precision.
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We find the closest approach by stepping through 10s-spaced data.
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The REAL TCA is between two steps. Our step-based TCA has up to 10s error.
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For a conjunction with ~10 km/s relative velocity, 10s uncertainty means
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~100 km position uncertainty — completely unacceptable for CA.
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This test measures how much the miss distance changes around TCA to show
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that step-based TCA finding is not sufficient for mission use. *)
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let test_tca_precision () =
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let oem1 = parse_oem "conjunction_sat1.oem" in
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let oem2 = parse_oem "conjunction_sat2.oem" in
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let sv1 = Odm.state_vectors (List.hd (Odm.segments oem1)) in
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let sv2 = Odm.state_vectors (List.hd (Odm.segments oem2)) in
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let n = min (Array.length sv1) (Array.length sv2) in
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let min_i = ref 0 in
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let min_dist = ref Float.infinity in
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for i = 0 to n - 1 do
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let d = vec3_norm (vec3_sub sv1.(i).Odm.pos sv2.(i).pos) in
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if d < !min_dist then (
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min_dist := d;
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min_i := i)
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done;
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(* Check distance at adjacent steps *)
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let d_before =
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if !min_i > 0 then
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vec3_norm (vec3_sub sv1.(!min_i - 1).Odm.pos sv2.(!min_i - 1).pos)
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else !min_dist
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in
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let d_after =
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if !min_i < n - 1 then
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vec3_norm (vec3_sub sv1.(!min_i + 1).Odm.pos sv2.(!min_i + 1).pos)
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else !min_dist
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in
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let delta_before = d_before -. !min_dist in
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let delta_after = d_after -. !min_dist in
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Printf.printf " Distance at TCA-10s: %.3f km (+%.3f km from min)\n" d_before
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delta_before;
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Printf.printf " Distance at TCA: %.3f km\n" !min_dist;
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Printf.printf " Distance at TCA+10s: %.3f km (+%.3f km from min)\n" d_after
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delta_after;
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(* The miss distance changes by 10s of km in one time step.
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This shows the actual TCA is between steps and our step-based
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approach misses it. For mission CA, we need interpolation-based
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TCA refinement (e.g., quadratic fit around the minimum). *)
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let max_delta = Float.max delta_before delta_after in
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Printf.printf
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" Miss distance changes by %.1f km in 10s — step-based TCA is imprecise\n"
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max_delta;
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if max_delta > 1.0 then
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Printf.printf
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" WARNING: >1 km variation in 10s — need TCA refinement for mission CA\n"
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(* MISSION-READY TEST: Pc computation gap.
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Real conjunction assessment requires covariance matrices to compute Pc.
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GMAT OEMs don't include covariance — we can't compute Pc from OEMs alone.
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This test documents the gap: we have positions but no uncertainty estimate.
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Without covariance, the miss distance alone is meaningless for CA decisions.
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A 50 km miss distance could be Pc=1e-3 (bad) or Pc=1e-10 (fine) depending
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on covariance size. *)
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let test_pc_requires_covariance () =
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(* We can compute miss distance from GMAT OEMs *)
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let oem1 = parse_oem "conjunction_sat1.oem" in
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let oem2 = parse_oem "conjunction_sat2.oem" in
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let sv1 = Odm.state_vectors (List.hd (Odm.segments oem1)) in
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let sv2 = Odm.state_vectors (List.hd (Odm.segments oem2)) in
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let n = min (Array.length sv1) (Array.length sv2) in
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let min_dist = ref Float.infinity in
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for i = 0 to n - 1 do
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let d = vec3_norm (vec3_sub sv1.(i).Odm.pos sv2.(i).pos) in
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if d < !min_dist then min_dist := d
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done;
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Printf.printf " Miss distance: %.3f km\n" !min_dist;
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Printf.printf " Pc: CANNOT COMPUTE — no covariance in OEM\n";
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Printf.printf
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" GAP: Need GMAT covariance propagation (Propagate ... Covariance)\n";
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Printf.printf
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" or CDM with covariance to test ocaml-collision Pc computation.\n";
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(* This test passes but documents the gap. The real test would be:
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1. Generate GMAT OEM WITH covariance
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2. Construct a CDM from the GMAT data
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3. Compute Pc with ocaml-collision
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4. Compare against GMAT's Pc *)
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Alcotest.(check bool)
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"miss distance computed" true
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(Float.is_finite !min_dist)
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let () =
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Alcotest.run "collision-gmat"
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[
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( "conjunction",
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( "plumbing",
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[
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Alcotest.test_case "parse both OEMs" `Quick test_parse_both;
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Alcotest.test_case "minimum distance" `Quick test_minimum_distance;
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Alcotest.test_case "relative velocity" `Quick test_relative_velocity;
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] );
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( "mission-ready",
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[
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Alcotest.test_case "TCA precision" `Quick test_tca_precision;
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Alcotest.test_case "Pc requires covariance" `Quick
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test_pc_requires_covariance;
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] );
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]