diff --git a/schainc/_noise.c b/schainc/_noise.c
index 97e07a0..66ee196 100644
--- a/schainc/_noise.c
+++ b/schainc/_noise.c
@@ -10,9 +10,9 @@ static PyObject *hildebrand_sekhon(PyObject *self, PyObject *args) {
   if (!PyArg_ParseTuple(args, "Od", &data_obj, &navg)) {
       return NULL;
   }
-  
+
   data_array = PyArray_FROM_OTF(data_obj, NPY_FLOAT64, NPY_IN_ARRAY);
-  
+
   if (data_array == NULL) {
       Py_XDECREF(data_array);
       Py_XDECREF(data_obj);
@@ -49,18 +49,17 @@ static PyObject *hildebrand_sekhon(PyObject *self, PyObject *args) {
   // return PyLong_FromLong(lnoise);
   return PyFloat_FromDouble(lnoise);
 }
-/*
+
 static PyObject *hildebrand_sekhon2(PyObject *self, PyObject *args) {
   double navg;
-  double th;
   PyObject *data_obj, *data_array;
 
-  if (!PyArg_ParseTuple(args, "Od", &data_obj, &navg, &th)) {
+  if (!PyArg_ParseTuple(args, "Od", &data_obj, &navg)) {
       return NULL;
   }
-  
+
   data_array = PyArray_FROM_OTF(data_obj, NPY_FLOAT64, NPY_IN_ARRAY);
-  
+
   if (data_array == NULL) {
       Py_XDECREF(data_array);
       Py_XDECREF(data_obj);
@@ -68,7 +67,7 @@ static PyObject *hildebrand_sekhon2(PyObject *self, PyObject *args) {
   }
   double *sortdata = (double*)PyArray_DATA(data_array);
   int lenOfData = (int)PyArray_SIZE(data_array) ;
-  double nums_min = lenOfData*th;
+  double nums_min = lenOfData*0.75;
   if (nums_min <= 5) nums_min = 5;
   double sump = 0;
   double sumq = 0;
@@ -94,13 +93,14 @@ static PyObject *hildebrand_sekhon2(PyObject *self, PyObject *args) {
 
   Py_DECREF(data_array);
 
-  // return PyLong_FromLong(lnoise);
-  return PyFloat_FromDouble(j,sortID);
+  return PyLong_FromLong(j);
+
 }
-*/
+
 
 static PyMethodDef noiseMethods[] = {
   { "hildebrand_sekhon", hildebrand_sekhon, METH_VARARGS, "Get noise with hildebrand_sekhon algorithm" },
+  { "hildebrand_sekhon2", hildebrand_sekhon2, METH_VARARGS, "Get index for satellite cleaning" },
   { NULL, NULL, 0, NULL }
 };
 
diff --git a/schainpy/model/data/jrodata.py b/schainpy/model/data/jrodata.py
index f3a0452..3f70377 100644
--- a/schainpy/model/data/jrodata.py
+++ b/schainpy/model/data/jrodata.py
@@ -192,9 +192,9 @@ class JROData(GenericData):
     data = None
     nmodes = None
     metadata_list = ['heightList', 'timeZone', 'type']
-    codeList = None
-    azimuthList = None
-    elevationList = None
+    codeList = []
+    azimuthList = []
+    elevationList = []
 
     def __str__(self):
 
@@ -489,7 +489,7 @@ class Spectra(JROData):
         return noise
 
     def getNoise(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None):
-        
+
         if self.noise_estimation is not None:
             # this was estimated by getNoise Operation defined in jroproc_spectra.py
             return self.noise_estimation
diff --git a/schainpy/model/graphics/jroplot_parameters.py b/schainpy/model/graphics/jroplot_parameters.py
index 93e9230..e8bf6da 100644
--- a/schainpy/model/graphics/jroplot_parameters.py
+++ b/schainpy/model/graphics/jroplot_parameters.py
@@ -87,7 +87,10 @@ class PowerPlot(RTIPlot):
         data = {
             'pow': 10*numpy.log10(dataOut.data_pow)
         }
-        data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
+        try:
+            data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
+        except:
+            pass 
         return data, {}
 
 class SpectralWidthPlot(RTIPlot):
diff --git a/schainpy/model/graphics/jroplot_spectra.py b/schainpy/model/graphics/jroplot_spectra.py
index c758b2d..6b0c4a7 100644
--- a/schainpy/model/graphics/jroplot_spectra.py
+++ b/schainpy/model/graphics/jroplot_spectra.py
@@ -23,6 +23,8 @@ class SpectraPlot(Plot):
     plot_type = 'pcolor'
     buffering = False
     channelList = []
+    elevationList = []
+    azimuthList = []
 
     def setup(self):
 
@@ -43,6 +45,10 @@ class SpectraPlot(Plot):
     def update_list(self,dataOut):
         if len(self.channelList) == 0:
             self.channelList = dataOut.channelList
+        if len(self.elevationList) == 0:
+            self.elevationList = dataOut.elevationList
+        if len(self.azimuthList) == 0:
+            self.azimuthList = dataOut.azimuthList
 
     def update(self, dataOut):
 
@@ -110,7 +116,10 @@ class SpectraPlot(Plot):
                     ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y)
                 if self.CODE == 'spc_moments':
                     ax.plt_mean.set_data(mean, y)
-            self.titles.append('CH {}: {:3.2f}dB'.format(self.channelList[n], noise))
+            if len(self.azimuthList) > 0 and len(self.elevationList) > 0:
+                self.titles.append('CH {}: {:2.1f}elv {:2.1f}az {:3.2f}dB'.format(self.channelList[n], noise, self.elevationList[n], self.azimuthList[n]))
+            else:
+                self.titles.append('CH {}:  {:3.2f}dB'.format(self.channelList[n], noise))
 
 
 class CrossSpectraPlot(Plot):
@@ -226,6 +235,8 @@ class RTIPlot(Plot):
     plot_type = 'pcolorbuffer'
     titles = None
     channelList = []
+    elevationList = []
+    azimuthList = []
 
     def setup(self):
         self.xaxis = 'time'
@@ -242,7 +253,12 @@ class RTIPlot(Plot):
 
     def update_list(self,dataOut):
 
-        self.channelList = dataOut.channelList
+        if len(self.channelList) == 0:
+            self.channelList = dataOut.channelList
+        if len(self.elevationList) == 0:
+            self.elevationList = dataOut.elevationList
+        if len(self.azimuthList) == 0:
+            self.azimuthList = dataOut.azimuthList
 
 
     def update(self, dataOut):
@@ -265,12 +281,18 @@ class RTIPlot(Plot):
 
         try:
             if self.channelList != None:
-                self.titles = ['{} Channel {}'.format(
-                    self.CODE.upper(), x) for x in self.channelList]
+                if len(self.elevationList) > 0 and len(self.azimuthList) > 0:
+                    self.titles = ['{} Channel {} ({:2.1f} Elev,  {:2.1f} Azth)'.format(
+                        self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList]
+                else:
+                    self.titles = ['{} Channel {}'.format(
+                        self.CODE.upper(), x) for x in self.channelList]
         except:
             if self.channelList.any() != None:
+
                 self.titles = ['{} Channel {}'.format(
                     self.CODE.upper(), x) for x in self.channelList]
+
         if self.decimation is None:
             x, y, z = self.fill_gaps(self.x, self.y, self.z)
         else:
@@ -532,7 +554,7 @@ class SpectraCutPlot(Plot):
                 labels = ['Range = {:2.1f}km'.format(y[i]) for i in index]
                 self.figures[0].legend(ax.plt, labels, loc='center right', prop={'size': 8})
             else:
-                for i, line in enumerate(ax.plt):            
+                for i, line in enumerate(ax.plt):
                     line.set_data(x, z[n, :, index[i]])
             self.titles.append('CH {}'.format(self.channelList[n]))
         plt.suptitle(self.maintitle,  fontsize=10)
@@ -879,6 +901,8 @@ class NoiselessRTIPlot(Plot):
     plot_type = 'pcolorbuffer'
     titles = None
     channelList = []
+    elevationList = []
+    azimuthList = []
 
     def setup(self):
         self.xaxis = 'time'
@@ -894,9 +918,12 @@ class NoiselessRTIPlot(Plot):
             self.CODE.upper(), x) for x in range(self.nplots)]
 
     def update_list(self,dataOut):
-
-        self.channelList = dataOut.channelList
-
+        if len(self.channelList) == 0:
+            self.channelList = dataOut.channelList
+        if len(self.elevationList) == 0:
+            self.elevationList = dataOut.elevationList
+        if len(self.azimuthList) == 0:
+            self.azimuthList = dataOut.azimuthList
 
     def update(self, dataOut):
         if len(self.channelList) == 0:
@@ -906,9 +933,15 @@ class NoiselessRTIPlot(Plot):
 
         n0 = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
         (nch, nff, nh) = dataOut.data_spc.shape
+        #print(nch, nff, nh)
+        if nch != 1:
+            aux = []
+            for c in self.channelList:
+                aux.append(n0[c]) 
+            n0 = numpy.asarray(aux)
         noise = numpy.repeat(n0,nh, axis=0).reshape((nch,nh))
-
-
+        #print(dataOut.elevationList, dataOut.azimuthList)
+        #print(dataOut.channelList)
         data['noiseless_rti'] = dataOut.getPower() - noise
         data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
         return data, meta
@@ -923,10 +956,15 @@ class NoiselessRTIPlot(Plot):
 
         try:
             if self.channelList != None:
-                self.titles = ['{} Channel {}'.format(
-                    self.CODE.upper(), x) for x in self.channelList]
+                if len(self.elevationList) > 0 and len(self.azimuthList) > 0:
+                    self.titles = ['{} Channel {} ({:2.1f} Elev,  {:2.1f} Azth)'.format(
+                        self.CODE.upper(), x, self.elevationList[x], self.azimuthList[x]) for x in self.channelList]
+                else:
+                    self.titles = ['{} Channel {}'.format(
+                        self.CODE.upper(), x) for x in self.channelList]
         except:
             if self.channelList.any() != None:
+
                 self.titles = ['{} Channel {}'.format(
                     self.CODE.upper(), x) for x in self.channelList]
         if self.decimation is None:
diff --git a/schainpy/model/proc/jroproc_spectra.py b/schainpy/model/proc/jroproc_spectra.py
index 6f1d952..2a557ac 100644
--- a/schainpy/model/proc/jroproc_spectra.py
+++ b/schainpy/model/proc/jroproc_spectra.py
@@ -17,6 +17,8 @@ import math
 from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation
 from schainpy.model.data.jrodata import Spectra
 from schainpy.model.data.jrodata import hildebrand_sekhon
+from schainpy.model.data import _noise
+
 from schainpy.utils import log
 
 from scipy.optimize import curve_fit
@@ -1092,6 +1094,7 @@ class IntegrationFaradaySpectra(Operation):
     n = None
     minHei_ind = None
     maxHei_ind = None
+    avg = 1.0
     factor = 0.0
 
     def __init__(self):
@@ -1184,10 +1187,10 @@ class IntegrationFaradaySpectra(Operation):
 
         return
 
-    def hildebrand_sekhon_Integration(self,data,navg, factor):
-
-        sortdata = numpy.sort(data, axis=None)
-        sortID=data.argsort()
+    def hildebrand_sekhon_Integration(self,sortdata,navg, factor):
+        #data debe estar ordenado
+        #sortdata = numpy.sort(data, axis=None)
+        #sortID=data.argsort()
         lenOfData = len(sortdata)
         nums_min = lenOfData*factor
         if nums_min <= 5:
@@ -1209,7 +1212,9 @@ class IntegrationFaradaySpectra(Operation):
             j += 1
         #lnoise = sump / j
         #print("H S done")
-        return j,sortID
+        #return j,sortID
+        return j
+
 
     def pushData(self):
         """
@@ -1256,7 +1261,11 @@ class IntegrationFaradaySpectra(Operation):
                     # if i==1 and j==0: #NOT CONSIDERING DC PROFILE AT CHANNEL 1
                     #     continue
                     buffer=buffer1[:,j]
-                    index,sortID=self.hildebrand_sekhon_Integration(buffer,1,self.factor)
+                    sortdata = numpy.sort(buffer, axis=None)
+                    sortID=buffer.argsort()
+                    index = _noise.hildebrand_sekhon2(sortdata,self.navg)
+
+                    #index,sortID=self.hildebrand_sekhon_Integration(buffer,1,self.factor)
 
                     indexes.append(index)
                     #sortIDs.append(sortID)
@@ -1272,7 +1281,7 @@ class IntegrationFaradaySpectra(Operation):
                 if indexmin != buffer1.shape[0]:
                     if self.nChannels > 1:
                         cspc_outliers_exist= True
-                        print("outliers cpsc")
+                        #print("outliers cspc")
                     ###sortdata=numpy.sort(buffer1,axis=0)
                     ###avg2=numpy.mean(sortdata[:indexmin,:],axis=0)
                     lt=outliers_IDs