In this series:

Direction finding (DF) refers to the determination of the direction from which a received signal was transmitted. As illustrated in Figure 1, the direction information from two (or more) receivers is often merged to compute the transmitter location via triangulation.

Direction Finding Triangulation for Transmitter Localization

Fig. 1. Direction finding triangulation for transmitter localization

As you can guess, DF algorithms are used in various military applications, such as locating hostile transmitters, for example. But DF is also used in a wide range of civilian applications:

  • Radio direction finding (RDF) is used in navigation systems for ships, small boats, and aircraft. Since low frequency radio signals travel very long distances and over the horizon, this is a particularly good choice for this application.
  • Emergency aid, for locating aircraft crashes and lost people.
  • DF algorithms are also widely used for wildlife tracking. This technique is used for studying the movement of radio-tagged animals.

This post is the first of two, and focuses on the correlative interferometer DF algorithm. First, we’ll review different direction finding techniques, and then we’ll discuss the advantages of the correlative interferometer algorithm. Finally, we’ll present an overview of a direction finding system.

In our second post, we’ll evaluate a possible FPGA algorithm implementation and discuss some hardware considerations.

A Review of Direction Finding Algorithms

 

Many direction finding applications require only a directional antenna (more sensitive in some directions than in others). The source of a transmission can be determined simply by rotating or moving the antenna until the maximum signal level is obtained. This solution is the cheapest one but also the least accurate. To get better direction resolution, much more sophisticated techniques are needed

[1].

The Doppler shift direction finding technique estimates the angle of arrival of the received signal by measuring the Doppler shift induced by a single moving antenna around a circle. As illustrated in Figure 2, the measured frequency of the received signal reaches its maximum value at point B since it is where the antenna is moving closer to the transmission source at its maximum speed. In contrast, the measured frequency is at its smallest value at point D since the antenna is moving away from the transmitter (see Figure 3). At positions A and C, no Doppler shift happens since the antenna is momentarily stationary relative to the transmitter.

Note that instead of having a single antenna physically moving in a circle, modern approaches use a multi-antenna circular array and sequentially switch between the antennas.

Doppler shift direction finding

Fig. 2. Doppler shift direction finding

 

Doppler shift seen at different positions in the circle (B and D)

Fig. 3. Doppler shift seen at different positions in the circle (B and D)

The Time Difference of Arrival (TDOA) method consists of deploying three or more receivers at different locations and measuring the time difference of the received signal. An accurate time reference is crucial, often derived from GPS.

The Watson-Watt technique works by measuring the magnitude of the signal along two orthogonal Adcock antenna pairs. The arctangent function of these two measures provides the signal bearing.

The basic principle of the correlative interferometer consists of two steps:

  1. Compute some phase differences of the signal received at multiple co-located antennas.
  2. Compare the measured phase differences with a reference data set. The reference is obtained for a DF system of known configuration at a known transmitter angle. Interpolation of the reference table can be used to get better accuracy.

The Advantages of the Correlative Interferometer Method

 

Correlative interferometry has many inherent performance advantages over the other techniques:

  • Typical accuracy is better than 1°. The accuracy is also better than other DF techniques in the presence of multipath fading, inter-channel interference and external noise sources for similar antenna diameters.
  • The measurement of the elevation is possible.
  • The antennas usually used cover very large frequency ranges.
  • The response time is faster than with the Doppler shift system since the antenna outputs are sampled simultaneously rather than sequentially.

Because of these numerous advantages, this is the technique we’ve selected for our FPGA implementation case study.

DF System Overview

 

The overall DF system is composed of the following elements:

  • An N-element antenna. Our implementation study assumes the use of a commercial five-element DF antenna such as those available from Aerosystems International Inc. These wide band antennas often cover from 20 MHz to 3.6 GHz.
  • An RF front end responsible for coherently filtering and downsampling the RF signals to the DAQ system.
  • An FPGA-based DAQ system that performs the analog to digital conversion (ADC) and the main processing of the algorithms. This is the subject of our second blog post.
  • A host PC, used to perform the last steps of the algorithm and to display the results. The host PC might also aggregate the angles of arrival of the received signal computed from different DF systems and perform the triangulation to estimate the location of the transmitter.

Conclusion

 

In this post, we briefly described the most popular techniques for today’s direction finding applications, with emphasis on the correlative interferometer algorithm. This technique mainly consists of computing the phase differences of the signal received at multiple co-located antennas, and then comparing the measured values with a reference table.

In a subsequent post, we’ll evaluate an FPGA implementation of the correlative interferometer algorithm core.

References

Denisowski, Paul. 2011. “A comparison of radio direction-finding technologies.” Dept. of Energy Spectrum Management Conference. Las Vegas. http://www.denisowski.org/Articles/Denisowski%20-%20Comparison%20of%20Radio%20Direction-Finding%20Technologies.pdf