Many thanks to Dale (N3HXZ) who shares the following guest post:
Does your antenna counterpoise orientation matter?
by Dale (N3HXZ)
I am an avid SOTA and POTA activator and love field operation. I use a portable vertical whip antenna with a single counterpoise for my antenna system and have always wondered if orienting my counterpoise would provide some signal strength gain in a particular direction. I decided to run a series of tests using WSPR to gather field data, and use statistics to answer the question:
Does one counterpoise orientation favor another in terms of average signal strength?
WSPR is a great tool for antenna testing. You can study various antenna configurations by making some WSPR transmissions and then checking the data on the WSPRnet database to see how well the signal was received at various stations located all over the world. You have to be careful in interpreting WSPR data though as receiving stations have different antenna and radio configurations, and the band propagation can vary rapidly at times. So how do you take advantage of all the data you receive from stations and draw some meaningful conclusions? I have found that using proven statistical theory in analyzing the transmitted signal strength received from individual stations can provide you results that you can confidently trust.
So what statistical algorithm is helpful?
For antenna signal strength comparison between two configurations, you can use an independent two-sample t-test with a one-tailed t-test evaluation. It sounds like a mouth-full, but it is quite simple. For our purposes, the t-test compares the average signal strength at a given receiving station from two different antenna configurations. The one-tailed test validates or invalidates the hypothesis that one antenna configuration produces an average signal strength greater or less than the other antenna configuration.
The testing requires that you run WSPR long enough to gather multiple reports at a single receiving station for both antenna configurations. Using the signal strength reports, you compute the average signal strength and the standard deviation of the signal strength over the sampled data points. Excel can easily provide that data. With this information and the number of sample points for each antenna configuration (they can be different), you then run a calculation by hand or in Excel to compute the ‘t’ value.
This ‘t’ value is then compared to a critical value for the number of sampling points from a ‘Students t table”. If the ‘t’ value is less than the critical value you can confidently conclude that the hypothesis is false and therefore conclude that there is no significant difference in the mean value of the signal strengths between the two. If the ‘t’ value is greater than the critical value you can accept the hypotheses that one antenna configuration produces a greater or less average signal strength than the other configuration.
For reference there is an easy to read article introducing the t-test. Another article gives example data and results from a t-test formula calculation. Lastly, you can reference the Students t table chart to determine the critical values to compare against you t test calculation.
Let’s now review the testing that was performed.
I used a 17’ vertical whip antenna configuration with a single counterpoise from the Chameleon MPAS Lite product. I ran two configurations with the counterpoise at 90 degrees to one-another. Please see Figure 1.
One set of tests was run with the “NE” counterpoise pointing north-east. The second set of tests was run using the “SE” counterpoise pointing to the south-east.
WSPR transmits for 110 seconds every 4th 2-minute cycle. Between transmissions I switched between counterpoise configurations to minimize band propagation fluctuations between data sets. I transmitted at 5 Watts on the 20M band. The WSPR session lasted roughly 2 hours and 15 minutes. I collected data from 63 stations with 205 reports from my QTH in Pittsburgh. A view of the stations receiving my transmissions is shown in Figure 2.
A sample of data received from a single station is shown in Table 1. The receiving station was NI5F in Graceville FL.
Six sets of signal strength (SNR in dB) data were collected for both counterpoise configurations. The average signal strength and standard deviation were calculated from Excel. The calculated t-test value is shown and the formula highlighted in the formula bar. The Students t-table is used to get the critical value. It requires the ‘degrees of freedom (df), which is the sum of the two data set counts minus 2. (6+6-2)=10.
A table look-up at a df=10 gives a critical value of 1.812 assuming a 95% confidence interval. The absolute value of the t-test (0.955) is less than the critical value (1.812). Therefore the ‘hypothesis’ that the average signal strength from the two counterpoise configurations is different is false; and the conclusion is that the mean value of the signal strengths for the two configurations are not significantly different.
An overall summary of five other stations is given in Table 2. Stations were selected from the three ‘quadrants’ pointing northeast, northwest, and southwest. (There were no reports from the southeast quadrant). These stations received signals with either the counterpoise pointing roughly in a line directed at their location, or in a line broadside to their location. In all cases, the hypothesis that the average signal strengths differed between counterpoise configurations were proven false. Hence, the overall conclusion is that the orientation of a single counterpoise for a vertical antenna does not measurably impact the average signal strength received by a given station.
Gathering signal strength data from WSPR and analyzing it with a proven statistical method provides a way to confidently assess the performance of one antenna configuration against another. The calculations are simple; you just need patience in collecting data over a couple hours!