The matlab file of the processed moored ADCP data contains the 
  following data structures: 
  
  beam_prop           
  bottom_track              
  sensor              
  settings            
  velocity          
  
  
  The structures contain the following fields:
  (note: the dimension "N" gives the number of profiles, which will vary for 
  different instrument and years)
  
  

1)	velocity:

       u: [8xN ]            zonal, eastward positive    
       v: [8xN ]            meridional, northward positive
    time: [Nx6 ]            [year, month, day, hour, min, sec] in GMT
    
    
2) settings: 
                      sn: 9999
                mooringID: 'bs3b'
                 cruiseID: 'aon10'
               time_start: [2009 8 5 0 0 0]
                 time_end: [2010 9 13 17 0 0]
                 position: [71 23.6270 -152 -3.8200]
                     bins: 20
       pings_per_ensemble: 60
                 bin_size: 5
                    blank: 2
                bin1_dist: 7.7100
    transmit_pulse_length: 4.7400
                    pgcut: 30
                    evcut: 0.1000
  
   "pgcut" and "evcut" refer to the thresholds for automatic
   editing based on percent_good and error velocity.


2) sensor:
               w: [8xN ]     vertical velocity
               e: [8xN ]     "error" velocity
           depth: [8xN ]     bin depths; usually slightly time dependent
              dz: [8x1 ]     bin distance from transducer (fixed in time)
            days: [Nx1 ]     year days; noon on Jan 1 = 1.5
         decdays: [Nx1 ]     "decimal days"; noon on Jan 1 = 0.5
          julian: [Nx1 ]     Julian days (e.g., Julian(2000,1,1,0,0,0)= 2451545)
           pitch: [Nx1 ]     transducer pitch
            roll: [Nx1 ]         "      roll
         heading: [Nx1 ]         "      heading
            temp: [Nx1 ]     transducer temperature
            salt: [Nx1 ]     microcat (MC) salinity, if available
          soundV: [Nx1 ]     sound velocity
         current: [Nx1 ]     ADCP current
        pressure: [Nx1 ]     from ADCP if available (e.g., LR75); otherwise from MC
        datenumT: [Nx1 ]     time in matlab's datenum format
        tr_depth: [Nx1 ]     transducer depth; from MC if ADCP (like WH300) has no pressure sensors
    conductivity: [Nx1 ]     microcat (MC) conductivity, if available
         MC_temp: [Nx1 ]     microcat temperature
          magvar: [Nx1 ]     magnetic deviation, eastward positive
             adc: [Nx8 ]     analog/digital converter output, with
                              1. Transmit current
                              2. Transmit voltage
                              3. Ambient temperature
                              4. Pressure (+)
                              5. Pressure (-)
                              6. Attitude temperature
                              7. Attitude
                              8. Contamination sensor 
          
          for "adc", we typically only look at transmit current and voltage. The other
          meaning of the other fields is unclear to me, and the manual does not help.
            

3) beam_prop            

   gives beam parameters backscatter amplitude ("echo"), target strength ("ts",
   a scaled version of echo that seeks to eliminate the normal decay of return
   echo with distance from the transducer), correlation,  and percent_good (the
   number of good pings within an ensemble average). The variables "mn_.." 
   contain the average over four beams.
            
    echo1: [8N ]
    echo2: [8N ]
    echo3: [8N ]
    echo4: [8N ]
    mn_ea: [8xN ]
      ts1: [8xN ]
      ts2: [8xN ]
      ts3: [8xN ]
      ts4: [8xN ]
    mn_ts: [8xN ]
    corr1: [8xN ]
    corr2: [8xN ]
    corr3: [8xN ]
    corr4: [8xN ]
    mn_co: [8xN ]
      pg1: [8xN ]
      pg2: [8xN ]
      pg3: [8xN ]
      pg4: [8xN ]



4) bottom_track:
 
    bt_range: [Nx4 ]
      bt_vel: [Nx4 ]
     bt_corr: [Nx4 ]
       bt_pg: [Nx4 ]