Continuous Wave Airport Surface Movement Radar

Author: Andre Adrian
Version: 6aug2006


An Airport Surface Movement Radars (ASMR) is a simple radar. A rotating antenna turns with 10 Revolutions per Minute (RpM) or faster. A magnetron generates a Radio Frequency (RF) pulse of 10GHz. This is the technology of 1960. The receiver is quite modern in terms of Moving Target Indication (MTI) and clutter suppression, but there is only so much you can do with a single frequency RF pulse that is more or less coherent.
A big reason for this ASMR technology is cost. This paper discusses how a modern ASMR can be build for the same price but with (hopefully) better performance. The radar design is based on Continuous Wave (CW) solid state transmitter and Field Programmable Gate Array (FPGA) hit processor. The waveform is pseudo noise. The target identification is done with a digital 1024 elements tapped-delay-line. The Least Means Square (LMS) algorithm in fixed point is used.
At the moment the project is in concept phase: the market is scanned for available Commercial of the Shelf (COTS) components to build a proof-of-concept radar with a RF frequency of 2.4GHz and 100 taps. Equipment for this RF frequency is very cheap because of IEEE 802.11b Wireless LAN (WLAN) .
The project has no resources yet. No money, no manpower. But this concept paper will hopefully open the money box...

ASMR Requirements

Range = 3Km
Range Resolution = 3m = minimum 50MHz bandwidth = minimum 100 Megasamples/s
Rotation = 30RpM = 2s scantime
Azimuth Resolution = 0.17° = 2048 steps per 360°
Radio Frequency = 10GHz
Minimum Target speed = 10km/h
Maximum Target speed = 270km/h

One range row is illuminated for 1ms. Therefore 100000 samples are available for filter learning.

ASMR Proof-of-Concept Requirements

The Proof-of-Concept radar shall show the working of the LMS algorithm for noise waveform CW radar in a near-live environment. Important topics to test are:
Range = 300m
Range Resolution = 3m = minimum 50MHz bandwidth = minimum 100 Megasamples/s
Rotation = 30RpM or slower
Azimuth Resolution = 0.17° or larger
Radio Frequency = 2.4GHz
Minimum Target speed = 10km/h
Maximum Target speed = 270km/h

Plant Simulation

For a radar, plant is the medium in which the radar signals travel on their way from transmitter to target to receiver. Another term for plant is channel, which is used in data communications.

The relation between transmitter, target and receiver can be simulated with two target dependent properties and the superposition principle. The distance between target and antennas determines the delay from signal transmit to signal receive. The Radar Cross Section (RCS) together with the distance determine the attenuation of the signal. If there are several targets that reflect radar energy back to the receiver, the receiver gets the sum (superposition) signal.

Discrete Plant Simulation with Tapped Delay Line

The discrete plant simulation is based on a tapped delay line. The distance between radar and target is simulated with a delay element line. The attenuation is simulated with multiplication with a delay element dependent constant factor w. The superposition is simulated with addition of all values.  Below is the typical structure of a tapped-delay-line or Finite Impulse Response (FIR) filter. The top row shows the attenuation values w, the second row contains the delay elements, the third row performs the attenuation multiplications and the last row calculates the superposition additions.

Radar as a System Identification Problem

The Least Means Square (LMS) algorithm can be used for system identification: Estimate the w values if only TX and RX signals are given. The w values form a "range row". After processing of 30000 to 100000 TX and RX samples the w vector has "learned" the delays and attenuations of the targets. The LMS filter is a FIR filter plus the adaptation (learning) structure. The output of the FIR filter is now the estimated RX signal. This is compared to the received RX signal. The resulting error signal e is attenuated by a constant value mikro. This mikro times e factor is now used to update all w values with the formula new_w = old_w + mikro * e * x. The value x is the delayed TX signal.
The LMS filter is the most simple adaptive filter. It has good robustness, but slow learning speed. Because of the large number of samples in the CW ASMR the slow learning speed is no problem.

Why Noise waveform radar?

The LMS algorithm performs system estimation. One important LMS application is echo cancellation. To speed up the learning of an LMS echo canceller, often pseudo noise is transmitted in front of real data. From information theory we know that white noise contains the most information of all wave forms. White noise gives the fastest learning of an LMS filter.
Still we should see the differences between white noise we transmit and noise we receive. The received signal is distorted by thermal receiver noise and noise from the medium, e.g. other transmitters on the same radio frequency. Signal distortion has a negative impact on range and azimuth resolution and even on useable range. In this aspect noise waveform radar is equal to pulse radar or CW-FM radar.
We can assume that for some distortions the CW-FM radar is superior, and for other distortions CW-Noise waveform has the leading edge. Important for the user of the radar are not all kinds of distortions, but the distortions that happen in real live under working conditions. The author assumes that for real live distortions CW-Noise waveform outperforms CW-FM chirps because noise is maximum information. You can't beat white noise!

CW-Noise waveform system diagram

The CW design needs a TX and a RX antenna. These antennas are mounted on a rotating antenna platform. The encoder gives the azimuth information to the hit processor. The noise waveform transmit signal is generated with an pseudo noise generator that changes the frequency of a voltage controlled oszillator (VCO). This design creates a single sideband RF signal. The power amplifier (PA) feeds the TX antenna. A small part of the transmit signal is coupled to the left down converter mixer. Because of range resolution the intermediate frequency (IF) amplifier bandwidth is 50MHz or even more. The design is wideband, not ultra wideband (UWB).
IF amplifier (AMP) and low pass filter (LPF) prepare the downconverted TX signal for the Analog Digital Converter (ADC) with is part of the demodulator.
The receiver signal flow is very standard: low noise amplifier (LNA), mixer, IF amplifier, low pass filter, ADC and demodulator.
The heart of the hit processor is the LMS filter. The 1024 LMS filter w values form the range cells. Together with the 2048 different azimuth values there are 1024*2048 = 2.1 million radar bins. With a scan time of 2 seconds (antenna rotates with 30RpM) and 2048 azimuth values one range row is illuminated for 1 millisecond. In this time the w values in the actual "range row" change. For the next 1999 milliseconds this range row rests in memory.
The radar bin information in the hit processor is copied to the moving target indication (MTI) processor, a dual CPU personal computer running Linux as operating system. One CPU does the MTI process, the other CPU does the radar bin to raster scan display conversion process.

Project Risks

At the moment there are no CW-Noise waveform ASMR on the marketplace to buy as COTS equipment. Maybe this is a sign that the idea is not working. Next to this "I don't want to be the first one" there are some more risks: