aspg-3-4350-1791940425 20261014011345 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2026 21 2 Mostafa Borhani Smart Tech Services, Muscat, Oman Normal false false false EN-US X-NONE AR-SA DefSemiHidden="false" DefQFormat="false" DefPriority="99" LatentStyleCount="371"> UnhideWhenUsed="true" QFormat="true" Name="heading 2"/> UnhideWhenUsed="true" QFormat="true" Name="heading 3"/> UnhideWhenUsed="true" QFormat="true" Name="heading 4"/> UnhideWhenUsed="true" QFormat="true" Name="heading 5"/> UnhideWhenUsed="true" QFormat="true" Name="heading 6"/> UnhideWhenUsed="true" QFormat="true" Name="heading 7"/> UnhideWhenUsed="true" QFormat="true" Name="heading 8"/> UnhideWhenUsed="true" QFormat="true" Name="heading 9"/> Name="index 1"/> Name="index 2"/> Name="index 3"/> Name="index 4"/> Name="index 5"/> Name="index 6"/> Name="index 7"/> Name="index 8"/> Name="index 9"/> UnhideWhenUsed="true" 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Colorful Accent 5"/> Name="Grid Table 7 Colorful Accent 5"/> Name="Grid Table 1 Light Accent 6"/> Name="Grid Table 6 Colorful Accent 6"/> Name="Grid Table 7 Colorful Accent 6"/> Name="List Table 1 Light Accent 1"/> Name="List Table 6 Colorful Accent 1"/> Name="List Table 7 Colorful Accent 1"/> Name="List Table 1 Light Accent 2"/> Name="List Table 6 Colorful Accent 2"/> Name="List Table 7 Colorful Accent 2"/> Name="List Table 1 Light Accent 3"/> Name="List Table 6 Colorful Accent 3"/> Name="List Table 7 Colorful Accent 3"/> Name="List Table 1 Light Accent 4"/> Name="List Table 6 Colorful Accent 4"/> Name="List Table 7 Colorful Accent 4"/> Name="List Table 1 Light Accent 5"/> Name="List Table 6 Colorful Accent 5"/> Name="List Table 7 Colorful Accent 5"/> Name="List Table 1 Light Accent 6"/> Name="List Table 6 Colorful Accent 6"/> Name="List Table 7 Colorful Accent 6"/> /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;} Infrastructure-based autonomous perception operates under fundamentally different constraints than vehicle mounted systems: elevated-mounting geometries producing depression-angle-dependent sparse point clouds, a 12.95 W IEEE 802.3af Power-over- Ethernet (PoE) power ceiling, and distributed asynchronous sensing governed by IEEE 1588v2 precision time protocol (PTP) synchronization uncertainty. Existing automotive radar–LiDAR fusion frameworks assume abundant power, dense sensing, and synchronous measurements — assumptions that all fail in fixed infrastructure deployments. This paper presents XADAR, an uncertainty-aware multi-modal fusion framework designed for these infrastructure-specific constraints. XADAR makes three princi-pal contributions: (1) a covariance inflation mechanism that propagates PTP synchronization uncertainty continuously through the fusion pipeline, replacing hard synchronization thresholds with a smooth degradation curve proportional to temporal offset; (2) adap-tive sensor-specific fusion weights derived from modality covariance matrices that account for IWR6843 77 GHz FMCW radar Doppler ambiguity and ground-reflection multipath, and TFS20-L ToF LiDAR atmospheric scattering and range-zone limitations; and (3) a complete reproducible architecture including an IEEE 802.3af-compliant power budget (5.78 W maximum concurrent load; 41.6% PoE safety margin), quantitative 77 GHz propagation analysis based on ITU-R P.676-12 and P.838-3 (10.7 dB fade margin at 100 m under 50 mm/hr rain), and an MIL-STD-1629 FMEA covering twelve failure modes with severity classifications. A structured five-stage validation pathway from synthetic temporal-offset experiments to sixmonth field trials is defined for future empirical work. 2026 476 488 4350 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.210229 https://americaspg.com/journal/3/article/4350 https://americaspg.com/storage/21778436396.pdf