论文/3batch

docs/paper/main.tex

@@ -49,7 +49,7 @@
   {\heiti\zihao{4} 摘\quad 要}
 \end{center}
 
-针对无线电干扰源的快速自动定位与清除问题，本文以测向观测的三值反馈
+无线电干扰源的测向与规划问题在生产和军事上的应用十分广泛。
 \texttt{no\_signal}、\texttt{near}、\texttt{direction} 为唯一信息来源，建立
 \textbf{有界误差交会定位—主动选点—覆盖证明搜索—动作耗时调度}的统一框架：四个问题
 复用同一几何内核，以覆盖证明与严格停止条件保证“清除所有干扰源”的硬约束，再优化

output/q3/practice/20260911-092448-bayes-port2026/effect_audit.json

@@ -0,0 +1,39 @@
+{
+  "strategy": "bayes",
+  "cleared_count": 12,
+  "cleared_channels": [
+    1,
+    3,
+    4,
+    5,
+    6,
+    7,
+    10,
+    11,
+    12,
+    16,
+    18,
+    20
+  ],
+  "all_clear_requests_succeeded": true,
+  "last_successful_clear_virtual_s": 4057.839246,
+  "last_successful_clear_wall_s": 3.1092007160186768,
+  "measures_through_last_clear": 98,
+  "measures_after_last_clear": 10225,
+  "extra_virtual_s_after_last_clear": 346169.8526,
+  "final_virtual_s": 350227.691846,
+  "accepted_actions": 10337,
+  "attempt_records": 10337,
+  "all_actions_first_attempt": true,
+  "timing_mismatches": 0,
+  "normal_exit": true,
+  "unresolved_channels": [],
+  "anomalies": [],
+  "official_total_source_count": 12,
+  "official_case_code": "J2WH-2K7D-5ZXS-DNK6",
+  "official_package_hash_matches": true,
+  "official_run_window_matches": true,
+  "all_official_sources_cleared": true,
+  "first_all_accounted_virtual_s": 4350.0,
+  "scope": "已核对官方问题3全向源结果、案例时间窗口和日志包哈希；12个官方源全部成功清除。"
+}

output/q3/practice/20260911-092448-bayes-port2026/execution.json

@@ -0,0 +1,4 @@
+{
+  "returncode": 0,
+  "wall_s": 105.03167799999937
+}

output/q3/practice/20260911-092448-bayes-port2026/practice-p3-7726693667322443561-J2WH-2K7D-5ZXS-DNK6.result.json

@@ -0,0 +1 @@
+{"version":2,"problem_no":3,"practice_run_no":7726693667322443561,"case_code":"J2WH-2K7D-5ZXS-DNK6","package_sha256":"2f375bc3ef6f174f36c2d13df319d1ad77ffe45d232750d001b86d68851e7dfe","window_started_at_utc":"2026-09-11T01:23:29.069Z","ended_at_utc":"2026-09-11T01:26:15.401Z","jammer_count":12,"omnidirectional_jammer_count":12,"directional_jammer_count":0}

output/q3/practice/20260911-092448-bayes-port2026/run_metadata.json

@@ -0,0 +1,115 @@
+{
+  "source": "official_practice",
+  "problem": 3,
+  "strategy": "bayes",
+  "robot_id": "202608023016",
+  "started_local": "2026-09-11T09:24:48.903286+08:00",
+  "git_head": "bd479b6d9dfc7951166d9704e2e62008592b99bc",
+  "config": {
+    "field": {
+      "omega_radius_m": 1800.0,
+      "channel_min": 1,
+      "channel_max": 20,
+      "source_count_min": 10,
+      "source_count_max": 16,
+      "r_eff_min_m": 1000.0,
+      "r_eff_max_m": 1500.0,
+      "near_radius_m": 5.0,
+      "clear_radius_m": 20.0,
+      "bearing_error_half_deg": 1.0,
+      "bearing_decimals": 2,
+      "coord_abs_limit_m": 2000000.0,
+      "directional_half_angle_deg": 90.0,
+      "max_virtual_duration_s": 360000.0,
+      "max_real_duration_s": 1200.0,
+      "test_window_s": 1500.0
+    },
+    "cost": {
+      "speed_mps": 5.0,
+      "measure_s": 5.0,
+      "switch_s": 1.0,
+      "clear_success_s": 5.0,
+      "clear_fail_s": 3.0
+    },
+    "session": {
+      "arena_id": "default",
+      "base_url": "http://127.0.0.1:2026",
+      "robot_id_max_bytes": 64,
+      "request_id_max_bytes": 128,
+      "request_body_max_bytes": 65536,
+      "connect_timeout_s": 5.0,
+      "read_timeout_s": 15.0,
+      "max_attempts": 3,
+      "retry_backoff_s": 0.25,
+      "reserve_exit_s": 60.0,
+      "real_rtt_p95_s": 1.0,
+      "self_test_real_budget_s": 1800.0
+    },
+    "search": {
+      "grid_step_m": 700.0,
+      "grid_half_cells": 3,
+      "fallback_clear_grid_m": 20.0,
+      "bearing_rounding_margin_deg": 0.005,
+      "polygon_sides": 192,
+      "witness_spacing_m": 60.0,
+      "candidate_rings": [
+        0.0,
+        0.4,
+        0.75,
+        1.0
+      ],
+      "candidate_angles": 12,
+      "clear_margin_m": 0.5,
+      "max_localize_steps": 8,
+      "max_anomalies_per_channel": 3,
+      "max_blocked_probes": 4,
+      "fallback_max_cells": 400,
+      "persistent_search": true,
+      "virtual_reserve_s": 10000.0
+    },
+    "bayes": {
+      "particle_spacing_m": 25.0,
+      "score_mode": "radius",
+      "score_subsample": 800,
+      "mc_representatives": 6,
+      "lambda_move_s": 0.1,
+      "wide_rings": [
+        1.0,
+        1.5,
+        2.0
+      ],
+      "station_ring_radius_m": 1200.0,
+      "two_opt_enabled": true,
+      "two_opt_passes": 3,
+      "grid_cert_enabled": true
+    }
+  },
+  "source_sha256": {
+    "src\\mcm26b\\__init__.py": "a1ea628e2b44a8b288c59fcda19a8f02b53f2d6fec675ef1e8c481ffdcbd7f35",
+    "src\\mcm26b\\belief\\__init__.py": "8613467122928e70dd2b07f14e1009a1edddb1d495d44f063f222fb118f78ba5",
+    "src\\mcm26b\\cli.py": "677b559233561fba1583aee6eeb215810c6e2ad82db5924f5c2e460e806d5f28",
+    "src\\mcm26b\\config.py": "4bdc6302e828826ab9b1552f94722a66e57f8b186778547e008452a031ba5540",
+    "src\\mcm26b\\coverage\\__init__.py": "ef24a48e91a099ca58a1fd9b5efa01b0bd76c21f63bd5febd444026281ec18c7",
+    "src\\mcm26b\\evaluation\\__init__.py": "3d7d9103675e4731f65ceacaac76c97096e244d0902e37d62376ea60b0a42217",
+    "src\\mcm26b\\geometry\\__init__.py": "c8f8d3e6320acb44fe9c14261116f8a668fdd59304e1d5b0318d8d50ea89b25c",
+    "src\\mcm26b\\geometry\\__main__.py": "41967f321b05abe515d2f0c10839b94c1e5c55a4c760b17345e0815f62acd676",
+    "src\\mcm26b\\geometry\\localization.py": "019a04a4205ca5cfb5832c7e2337e6ae3274ef9bdae1981c3764b8df8c2afd97",
+    "src\\mcm26b\\geometry\\planning.py": "5d6a11b2c4633c4f27bb4a61f77f4fbd20cfdce653d839845a735f9f1d3be2d1",
+    "src\\mcm26b\\particles.py": "c2cfabb07154883d4293f5c739b8ab06bd4b467c773365e1d4c153a0bd0fc30b",
+    "src\\mcm26b\\planner\\__init__.py": "bdd36737b2a8562612634d45290bf7165ee81c80fa8e7bcb9fcc9f4001390cda",
+    "src\\mcm26b\\planner\\bayes_loop.py": "068cde2bbcbea0333193b5d3d6ec850d8e310fb1368f682fcaa4f5f0fd90379b",
+    "src\\mcm26b\\planner\\seven.py": "cc143ce0703f231d8b5444ac6a2b2f4925cabf1556e58b0ea5166a510e6933f0",
+    "src\\mcm26b\\protocol\\__init__.py": "67423a0fe7f3ee3c7b1c0439da9554dab4bc30a09c5f3720d69e11076a36de0c",
+    "src\\mcm26b\\protocol\\client.py": "a486694b570bc00286ad30d4be04b01687ef3801d95154e75caa6209314dac36",
+    "src\\mcm26b\\protocol\\log.py": "0eb51302a0bdfa3c680b7726d0be59cebe6fdc6197fd9643a4d5cc0646e34ac3",
+    "src\\mcm26b\\protocol\\rules.py": "7941a4cddafd875dedf0c57aa90e640cb5e22201800d3eb300dac313db19e6a3",
+    "src\\mcm26b\\protocol\\state.py": "dc4c50f38cc1014af848f21d3f972b2f51fba28b0feb3320ce85bf51389d3d34",
+    "src\\mcm26b\\protocol\\timing.py": "49fb1ca99db9db273364ddb27281b95e6e76099c16ce7fccddccbfe105d604ac",
+    "src\\mcm26b\\protocol\\transport.py": "668a8ab280e5e42a7994d7cedc0f487af19b140622d76b04da0dbbea3ad4940f",
+    "src\\mcm26b\\sim\\__init__.py": "7adcbaab5b94d4006ff926306a43c1042182be14789026e71885ed69389a6d55",
+    "src\\mcm26b\\sim\\playback.py": "073b74c149334604cd678c218e112f69d64fe907ef7c3b6f42b69470e48fbb7a",
+    "src\\mcm26b\\sim\\scenes.py": "0647bd19409acb5160625dd39e71157aeb20f9e979e82a7fe86aaec75a1cbf32",
+    "src\\mcm26b\\sim\\simulator.py": "553bf9fbb9fd4875a6ec68792e90a08287e5b87c749ffda9a7556b582a5ecba3",
+    "src\\mcm26b\\sim\\transport.py": "889c06965fdb905f5d9fa8e947940ea68be216f60a487340c2f326b6e8a9a36d"
+  }
+}