Figure 8: diagram of a phase-coded pulse compression
Phase-coded waveforms differ from FM waveforms in that the long pulse is sub-divided into a number of shorter sub pulses. Generally, each sub pulse corresponds with a range bin. The sub pulses are of equal time duration; each is transmitted with a particular phase. The phase of each sub-pulse is selected in accordance with a phase code. The most widely used type of phase coding is binary coding.
The binary code consists of a sequence of either +1 and -1. The phase of the transmitted signal alternates between 0 and 180° in accordance with the sequence of elements, in the phase code, as shown on the figure. Since the transmitted frequency is usually not a multiple of the reciprocal of the sub pulse width, the coded signal is generally discontinuous at the phase-reversal points.
The selection of the so called random 0, π phases is in fact critical. A special class of binary codes is the optimum, or Barker, codes. They are optimum in the sense that they provide low sidelobes, which are all of equal magnitude. Only a small number of these optimum codes exist. They are shown on the beside table. A computer based study searched for Barker codes up to 6000, and obtained only 13 as the maximum value.
It will be noted that there are none greater than 13 which implies a maximum compression ratio of 13, which is rather low. The sidelobe level is -22.3 db.
Radar complexity
Radar — an old acronym for radio detection and ranging — has always been a demanding technology, but at no time more so than today. Essentially, it works by emitting radio frequency (RF) signals at particular frequencies, and then listening for the signal's return — or "bounce" — off of targets of interest. At it simplest theoretical level, this does not sound like a big deal, but putting the theory into useful practice is where advanced technology — and designers headaches — come in.
Several different kinds of radar systems are in use today, including continuous wave (CW), pulsed, pulsed-Doppler, phased array, and synthetic aperture.
The Mercury RACE++ Series PowerStream 510 system is used in applications such as advanced radar, sonar, imaging, and inspection.
CW radar continually transmits energy toward the desired target and receives a reflection of this "continuous wave." These kinds of radar are useful for determining a target's velocity by using the Doppler effect to compare differences in the transmitted and received signals. These radar systems, however, have difficulty determining the target's range, or how far way it is.
Pulsed radar, on the other hand, sends out a series of short RF pulses. By measuring how long it takes to receive the returns from these pulses, system operators can estimate the range to the target. Pulse Doppler radar, in addition, uses Doppler shifts with radar pulses to determine the velocities of moving targets. These systems can determine the velocities, angles, and ranges of targets. These added capabilities, however, make pulse Doppler radar much more compute-intensive than simple pulsed radar.
Phased array radar systems, meanwhile, arrange large numbers of transceiver modules arranged on flat or curved surface. The system controls the phase — or a slight variation in the transmit and receive time of groups of transceiver modules — with computer commands, and in essence "steers" the radar beams quickly, enabling the phased array radar to scan specific areas quickly, "stare" at targets of interest, or do a variety of other tasks, all without the need to move the transceiver array mechanically.
The ability of phased array radar systems to manipulate their groups of transceivers also gives this system an "adaptive array" capability, which not only can steer beams quickly, but also enables the system to shift the focus of radar beams to "null out" electronic interference or jamming.
Precise radar images most often come from synthetic aperture radar systems. These so-called "side-looking" aircraft-mounted systems — such as the U.S. Joint Surveillance and Target Attack Radar System known as Joint STARS — produce two-dimensional images, where one dimension is the range, or distance from the radar to the target using Doppler processing, and the other dimension is the azimuth, which requires a physically large antenna to focus the transmitted and received RF signal into a sharp beam. Synthetic aperture radar, better known as SAR — collects data over a long distance, and processes the data as if it came from a physically long antenna. SAR requires extremely fast processing and very fast signal sampling rates.
After all this, the way in which a radar system processes information also can change the nature of the radar system itself. Take radar pulse compression, for example. This is a technique that makes the most of the radar's sensitivity and resolution by balancing the effects of radar pulse duration, radar pulse power, and radar pulse bandwidth.
Pulse compression uses Fast Fourier Transform (FFT) processing to massage the signal as it comes in from the A-D converters. "With pulse compression, you need to take an FFT of the radar signal to remove as much stuff that doesn't belong to the return signals as possible," explains Rodger Hosking, vice president of Pentek Inc. of Upper Saddle River, N.J., which supplies single-board processors to radar designers.
"So they send out a 'chirp', or a unique signal that doesn't exist in nature," Hosking continues. "You convert what comes back into frequency domain, and take the frequency domain of your outgoing pulse and correlate the two. You extract only the part of the signal coming back that has to do with the outgoing pulse. Then you do an inverse FFT, and you get a very nice 'blip'." Until recently, Hosking explains, that kind of processing has been done in analog, and in DSPs. "It's a very demanding problem to do in real time."
Processing challenges
One of the first and most serious problems confronting radar systems involves noise and clutter in the return signal. After all, RF energy bounces off a lot more than simply the target of interest; it bounces off trees, buildings, mountains, vehicles, and about anything else in its path, and in various degrees of intensity depending on the reflecting materials.
One of the most important tasks of modern radar systems is to reject, or "filter-out,"
return signals that are not of interest. Next, radar users today want far more from their systems than simply the proverbial "blip on the screen." Many modern radar systems are able to filter their return signals so finely that these signals produce an actual image of the target.
Finally, most radar systems — particularly those for military and aerospace applications — must operate in real time. All these factors combine to produce a challenge of staggering computational intensity for all but the simplest radar systems.
Today's radar systems digitize their signals very quickly after receiving them. After analog-to-digital conversion, advanced algorithms process the signals to eliminate noise by filtering out unwanted portions of the signal, perform Doppler calculations to help determine range, and do many other operations to prepare the data for further processing later that will do tasks like enter radar signatures into databases and display the information on graphical screens.
In the front-end "pre-processing" stage, the processor of choice increasingly is the field programmable gate array (FPGA) from companies such as Xilinx Inc. in San Jose, Calif., and Actel Corp. in Sunnyvale, Calif. This is primarily a move away from DSPs on the front end, experts say. At the same time, systems designers rely more heavily than ever before on high-end general-purpose processors such as the Altivec on the back end.