Pith Number

pith:X4R25S6H

pith:2026:X4R25S6HP7BY2KIFZXVB2LWGA4

not attested not anchored not stored refs resolved

Active Sensing with Meta-Reinforcement Learning for Emitter Localization from RF Observations

Alexander Mattick, Christian Wielenberg, Christopher Mutschler, Felix Ott, Lucas Heublein, M. Shamail J. Khan, Nisha L. Raichur, Tobias Feigl

An RL agent localizes GNSS interference sources by choosing sequential RF sensing actions from a 2x2 antenna.

arxiv:2605.12569 v1 · 2026-05-12 · eess.SP · cs.AI

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\pithnumber{X4R25S6HP7BY2KIFZXVB2LWGA4}

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4 Citations open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

the proposed method achieves a localization success rate of 80.1%, demonstrating the potential of RL for adaptive GNSS interference localization

C2weakest assumption

The Sionna ray-tracing simulation accurately captures real-world RF propagation, multipath effects, and domain shift conditions for the localization task to transfer beyond simulation.

C3one line summary

A meta-reinforcement learning agent achieves 80.1% success in localizing RF emitters by sequentially sensing the environment with a 2x2 patch antenna in Sionna ray-tracing simulations.

References

28 extracted · 28 resolved · 2 Pith anchors

[1] Impact and Detection of GNSS Jammers on Consumer Grade Satellite Navigation Receivers, 2016

[2] Varia- tional & Generative Models with Quantization for Disentanglement and Compressed Sensing of GNSS Spectrograms, 2026

[3] GNSS Interference Mitigation: A Measurement and Position Domain Assessment, 2021

[4] An Assessment of Impact of Adaptive Notch Filters for Interference Removal on the Signal Processing Stages of a GNSS Receiver, 2020

[5] Distortionless Space-Time Adaptive Processor Based on MVDR Beamformer for GNSS Receiver, 2017

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T03:10:01.801419Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

bf23aecbc77fc38d2905cdea1d2ec607118c8f4e99a26281b1957cc576d55fc0

Aliases

arxiv: 2605.12569 · arxiv_version: 2605.12569v1 · doi: 10.48550/arxiv.2605.12569 · pith_short_12: X4R25S6HP7BY · pith_short_16: X4R25S6HP7BY2KIF · pith_short_8: X4R25S6H

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/X4R25S6HP7BY2KIFZXVB2LWGA4 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: bf23aecbc77fc38d2905cdea1d2ec607118c8f4e99a26281b1957cc576d55fc0

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "96e4cfb62872217f76c4fe946b76d29bc3e6fd1f178478890b511e09700773d9",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "eess.SP",
    "submitted_at": "2026-05-12T10:03:41Z",
    "title_canon_sha256": "9b1883e5f23cd96b250f65a1e474f58cbeec6110f10587d9fb8fc64dd1e4400c"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12569",
    "kind": "arxiv",
    "version": 1
  }
}