add solution drafts, add component decomposition , add spec for other docs

docs/02_components/06_L2_Global_ReLocalization/spec.md

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+# L2 Global ReLocalization Component
+
+## Detailed Description
+**L2 Global ReLocalization** addresses the "Kidnapped Robot" problem. It is triggered when L1 fails (tracking lost) or periodically to drift-correct. It uses **AnyLoc (DINOv2 + VLAD)** to describe the current UAV image and queries the **Map Data Provider's** Faiss index to find the most similar satellite tiles.
+
+It does NOT give a precise coordinate, but rather a "Top-K" list of candidate tiles (coarse location).
+
+## API Methods
+
+### `localize_coarse`
+- **Input:** `frame: FrameObject`, `top_k: int`
+- **Output:** `List[CandidateLocation]`
+- **Description:**
+    1. Runs DINOv2 inference on the frame to get feature map.
+    2. Aggregates features via VLAD to get a global descriptor vector.
+    3. Queries Map Data Provider's Global Index.
+    4. Returns list of candidates.
+        - **CandidateLocation:** `{ tile_id: str, similarity_score: float, center_gps: LatLon }`
+- **Test Cases:**
+    - Input Frame A -> Returns Satellite Tile covering Frame A's location in Top-3.
+    - Input Black/Occluded Image -> Returns Low confidence or random.
+
+## Integration Tests
+- **Recall Test:** Run on dataset where ground truth is known. Verify that the correct tile is within the returned Top-5 for > 80% of queries.
+
+## Non-functional Tests
+- **Query Time:** Vector search must be extremely fast (< 50ms) even with large indices. DINOv2 inference is the bottleneck.
+