Conversion for Noise Temperature Te (K) to Noise Figure de KB2AH

     Te                 Te                Te              Te
    (K)          NF    (K)         NF    (K)             (K)          NF
      1    0.014949     51   0.703563    100 1.286666    150    1.810546
      2    0.029848     52   0.716281    101 1.297787    151    1.820405
      3    0.044696     53   0.728961    102 1.308880    152    1.830242
      4    0.059493     54   0.741604    103 1.319945    153    1.840057
      5    0.074240     55   0.754210    104 1.330982    154    1.849849
      6    0.088937     56   0.766781    105 1.341990    155    1.859620
      7    0.103584     57   0.779314    106 1.352971    156    1.869368
      8    0.118182     58   0.791812    107 1.363925    157    1.879095
      9    0.132731     59   0.804274    108 1.374850    158    1.888800
     10    0.147232     60   0.816700    109 1.385748    159    1.898483
     11    0.161684     61   0.829091    110 1.396619    160    1.908145
     12    0.176089     62   0.841446    111 1.407463    161    1.917785
     13    0.190446     63   0.853767    112 1.418280    162    1.927404
     14    0.204755     64   0.866052    113 1.429070    163    1.937002
     15    0.219018     65   0.878303    114 1.439833    164    1.946578
     16    0.233234     66   0.890520    115 1.450570    165    1.956133
     17    0.247403     67   0.902702    116 1.461280    166    1.965668
     18    0.261527     68   0.914850    117 1.471964    167    1.975182
     19    0.275604     69   0.926964    118 1.482621    168    1.984674
     20    0.289636     70   0.939045    119 1.493253    169    1.994146
     21    0.303623     71   0.951092    120 1.503858    170    2.003598
     22    0.317565     72   0.963105    121 1.514438    171    2.013029
     23    0.331463     73   0.975086    122 1.524992    172    2.022439
     24    0.345316     74   0.987033    123 1.535520    173    2.031829
     25    0.359125     75   0.998948    124 1.546023    174    2.041199
     26    0.372890     76   1.010830    125 1.556500    175    2.050549
     27    0.386612     77   1.022680    126 1.566953    176    2.059879
     28    0.400291     78   1.034498    127 1.577380    177    2.069188
     29    0.413926     79   1.046283    128 1.587782    178    2.078478
     30    0.427519     80   1.058037    129 1.598160    179    2.087748
     31    0.441070     81   1.069759    130 1.608512    180    2.096998
     32    0.454578     82   1.081449    131 1.618840    181    2.106229
     33    0.468045     83   1.093108    132 1.629144    182    2.115440
     34    0.481470     84   1.104736    133 1.639423    183    2.124631
     35    0.494853     85   1.116332    134 1.649678    184    2.133803
     36    0.508196     86   1.127898    135 1.659909    185    2.142956
     37    0.521497     87   1.139433    136 1.670116    186    2.152089
     38    0.534758     88   1.150938    137 1.680298    187    2.161203
     39    0.547979     89   1.162412    138 1.690457    188    2.170298
     40    0.561159     90   1.173855    139 1.700592    189    2.179375
     41    0.574299     91   1.185269    140 1.710704    190    2.188432
     42    0.587400     92   1.196653    141 1.720792    191    2.197470
     43    0.600462     93   1.208007    142 1.730857    192    2.206490
     44    0.613484     94   1.219332    143 1.740898    193    2.215491
     45    0.626468     95   1.230627    144 1.750917    194    2.224473
     46    0.639412     96   1.241893    145 1.760912    195    2.233437
     47    0.652319     97   1.253129    146 1.770884    196    2.242382
     48    0.665187     98   1.264337    147 1.780834    197    2.251309
     49    0.678017     99   1.275516    148 1.790761    198    2.260218
     50    0.690809    100   1.286666    149 1.800665    199    2.269108