Magnetic　positioning　approach　(MPA)　is　a　reliable　solution　for　automated　guided　vehicles　(AGVs)　under　relatively　fixed　route　conditions.　Ferrite　magnets　are　usually　buried　in　the　ground　and　employed　as　magnetic　nails　(MNs)　for　the　parking　and　steering　of　AGVs.　Our　previous　studies　implemented　a　novel　MPA　based　on　super-strong　NdFeB　magnets　and　the　minimize　iterations　between　magnetometer　data　and　predicted　values　via　the　magnetic　dipole　model,　with　the　advantage　of　more　exceptional　positioning　performance　than　traditional　MPAs.　Nevertheless,　the　iterative　optimization　algorithms　depend　on　the　initial　guess　setting;　besides,　the　complicated　calculation　based　on　multiple　magnetometer　data　makes　it　difficult　to　be　executed　on　a　microcontroller　in　real-time.　In　this　article,　we　propose　a　simplified　MPA　based　on　the　analytical　method.　The　analytical　expression　for　calculating　the　two-dimensional　position　of　an　MN　is　derived　from　the　magnetic　dipole　model.　Even　a　single　tri-axis　magnetometer　can　localize　the　MN,　whereas　multiple　magnetometers　tend　to　achieve　higher　positioning　performance.　Thus,　positioning　results　of　multiple　magnetometers　are　fused　based　on　the　confidence　criterion.　Comparing　with　the　MPA　based　on　the　Levenberg-Marquardt　algorithm,　the　proposed　MPA　could　achieve　comparable　positioning　accuracy　but　with　far　lower　computational　complexity　and　greater　robustness.　Thereby,　this　article　introduces　a　new　concept　of　high-precision　MPA　for　AGV　applications　without　the　complicated　visual　perception.