[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82945-en":3,"doc-seo-82945-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},82945,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","How Stable Is a PNT Resilience Score? Decision-Instability of Single-Number Resilience Ratings under Framework-Aligned Weighting","Every authoritative positioning, navigation, and timing (PNT) resilience framework defines resilience but relies on self-attestation, offering checklists and maturity Levels without an engine for measurement, evidence, or reproducible scoring. This work builds an open deterministic scoring engine atop a PNT simulator, producing per-dimension subscores with traceable scenarios, oracle provenance, and explicit validation status. It then tests whether a single composite score or a single maturity Level is stable for decisions across weighting and threat uncertainty, and analyzes failure modes.","How Stable Is a PNT Resilience Score? Decision-Instability of Single-Number Resilience Ratings under Framework-Aligned Weighting  \nChakshu Baweja  \nAshforde O¨U  \nTallinn, Estonia  \n[contact@ashforde.org](contact@ashforde.org)  \narXiv :2607 .05415v1 [ cs .CR] 22 Jun 2026  \nAbstract—Every authoritative positioning, navigation, and timing (PNT) resilience framework, from the DHS Resilient PNT Conformance Framework (RPCF) to the Resist-Detect-RespondRecover model and Yang’s resilient-PNT criteria, defines what resilience means but supplies only self-attestation: a checklist or a maturity Level, with no engine, no measurement, and no evidence. We build the missing measurement layer as an open, deterministic scoring engine over a PNT simulator, emitting perdimension sub-scores each traceable to a scenario and an oracle and each tagged with its honest validation status. We then ask whether a single composite score, or a single maturity Level, is a stable basis for a decision. Across a reference panel of seven architectures built to span genuine cross-dimension tradeoffs, a Dirichlet weighting simplex over the seven RPCF categories, anda five-threat ensemble, the answer separates into two regimes. The composite winner is stable under active denial and under near-equal weightings, flipping in about 1 percent of draws, so a single number is safe precisely where one design dominates; but re-weighting alone flips the winner in up to 22 percent of draws under nominal conditions, where designs genuinely contend, and that instability is a domain application of known compositeindicator sensitivity. The sharper and weighting-invariant failure is categorical: a weakest-link maturity Level (our minimumover-categories operationalization of the RPCF ladder, not the framework’s own rule) is a function of the threat assumed rather than of the architecture, changing for one architecture in seven across the ensemble. A constructed example shows that, because the composite rewards declared techniques, a singleband receiver declaring all seven techniques can outscore a genuinely more resilient system: self-attestation can be gamed by declaration. And apparent fourfold GNSS redundancy reduces, by the definition of a shared common-mode failure domain, to an effective diversity of one. The conclusions hold under a plusor-minus 20 percent perturbation of every driver within the modelled reduction. We argue for reporting per-dimension subscores with provenance and a rank range, not a phantom single number. This is a simulation-derived self-assessment aligned to RPCF v2.0, not a certification.  \nI. INTRODUCTION  \nA recurring gap runs through the PNT-resilience literature. Resilient PNT is a recognised national priority [2], and government, industry, and academic sources converge on the need for a quantified, reproducible, vendor-neutral resilience score checked against a published framework, yet  \nevery fielded instrument is self-attestation or pure concept. The DHS Resilient PNT Conformance Framework (RPCF) v2.0 [1] defines maturity Levels 0 to 4 and seven technique categories (Obfuscate, Limit, Verify, Isolate, Diversify, Mitigate, Recover) . The Resist-Detect-Respond-Recover (RDRR) function model [3] frames an assurance case as a documented body of evidence. Yang’s resilient-PNT concept [4] names availability, reliability, continuity, and accuracy criteria. None ships a measurement: a system owner declares conformance, or an assessor scores a questionnaire, and the result is a number nobody can reproduce.  \nThis invites a hazard that is rarely examined. To produce a single grade, the multi-dimensional, model-derived reality of a PNT system must be collapsed into one number or one Level. Composite-indicator methodology has long warned that such collapses are sensitive to the (arbitrary) weighting and aggregation choices [8], [9], [10], but the warning has not been quantified for PNT resilience, where the dimensions tradeoff in physically meaningful ways: a","cbCaif3WfnaNFOkl","https://ap.wps.com/l/cbCaif3WfnaNFOkl","pdf",239738,1,6,"English","en",105,"# Introduction\n## Gap in PNT resilience measurement\n## Frameworks and lack of reproducible scoring\n## Composite-indicator sensitivity as the motivation\n# Contributions and approach\n## Deterministic scoring engine and subscores\n## Decision stability study under weighting and threats\n## Reporting protocol from results","[{\"question\":\"Why do existing PNT resilience frameworks struggle to support reproducible scoring?\",\"answer\":\"They primarily rely on self-attestation (checklists, conformance declarations, or questionnaire-style assessment) rather than a measurement engine that produces evidence-backed, reproducible results.\"},{\"question\":\"What is the core contribution of the proposed approach?\",\"answer\":\"An open deterministic scoring engine that maps a PNT architecture and its simulated behavior to per-dimension subscores across RPCF categories, RDRR functions, and Yang’s criteria, with each subscore traceable to scenario and oracle and labeled by validation status.\"},{\"question\":\"When is a single composite score stable enough for decision-making?\",\"answer\":\"Stability holds in a regime where one design dominates, remaining stable under active denial and near-equal weightings, with winner flips occurring in roughly 1% of draws in the study.\"}]",1784184234,15,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"how-stable-is-a-pnt-resilience-score-decision-instability-of-single-number-resilience-ratings-under-framework-aligned-weighting","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/how-stable-is-a-pnt-resilience-score-decision-instability-of-single-number-resilience-ratings-under-framework-aligned-weighting/82945/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why do existing PNT resilience frameworks struggle to support reproducible scoring?","Question",{"text":75,"@type":76},"They primarily rely on self-attestation (checklists, conformance declarations, or questionnaire-style assessment) rather than a measurement engine that produces evidence-backed, reproducible results.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the core contribution of the proposed approach?",{"text":80,"@type":76},"An open deterministic scoring engine that maps a PNT architecture and its simulated behavior to per-dimension subscores across RPCF categories, RDRR functions, and Yang’s criteria, with each subscore traceable to scenario and oracle and labeled by validation status.",{"name":82,"@type":73,"acceptedAnswer":83},"When is a single composite score stable enough for decision-making?",{"text":84,"@type":76},"Stability holds in a regime where one design dominates, remaining stable under active denial and near-equal weightings, with winner flips 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