Compression with considerable sidelobe suppression effect in weather radar
© Wang et al.; licensee Springer. 2013
Received: 11 December 2012
Accepted: 26 February 2013
Published: 4 April 2013
Pulse compression is a classical topic. Because of its function in resolution enhancement, pulse compression technology has been applied in many kinds of radar such as pulse Doppler weather radar. In pulse compression, sidelobe suppression plays a key role for reducing clutter. In this article, a combination of two sidelobe suppression techniques for pulse compression is proposed. Simulation results show that the combination of the two techniques has better sidelobe suppression effectiveness.
KeywordsPulse compression Sidelobe suppression Weather radar
Radar, serving as a kind of method for detecting, has wide-range application areas such as military, aviation, geosciences, and so on. Pulse Doppler weather radar is an important device to detect clouds, wind fields, and precipitation. So, the resolution is very important for the forecasting of weather phenomena.
Pulse compression is useful for weather radar to increase the average transmitted power by transmitting a longer pulse but without reducing the range resolution of the radar. In general, peak power of solid-state transmitter or millimeter-wave klystron is not sufficient. Pulse compression is required to achieve the desired system sensitivity. Different coding schemes include linear frequency modulation (LFM), nonlinear FM. Frequency-modulated signals are characterized by their time bandwidth (TB) product which represents the ability to multiple signal-to-noise ratio (SNR).
For a radar pulse signal, after compression, the narrower pulse mainlobe is always accompanied by higher sidelobes. So, all pulse compression radars suffer from range side lobes which cause energy from strong reflections to leak into adjacent range cells. High suppression of side lobes is not required in some other non-meteorological radar, but is important for meteorological radar, because weather phenomena can have significant reflectivity gradients, and ground clutter echo can be between 35 and 55 dB much larger than medium rain. Furthermore, the side lobes of strong signal will falsely be recognized as an existence of small target. Therefore, range side lobes must be suppressed by a large amount to prevent contamination in adjacent range cells.
In this article, compression experiments are conducted on an LFM sample signal extracted from a period of echo of a weather radar. In these experiments, some sidelobe suppression algorithms are used. The algorithms include multiplying window in frequency domain, phase distortion, and frequency modification.
In Section 2, the data are analyzed and compression basing on matched filtering and windowed matched filtering are carried out. In Section 3, spectrum modification technique and phase predistortion technique are utilized, respectively, and the effects are analyzed. Then, the two techniques are combined in Section 4. Experiments are conducted on the real weather echo and the effects are compared. Section 5 is the conclusion.
2. LFM pulse and matched filtering compression
We found that the phase and the fitting curve superpose each other. This indicates that the linearity of the frequency is good and the pulse is a suitable LFM sample.
The amplitude of the first sidelobe is –17.4827 dB and the compression ratio is about 83.3.
A sidelobe of –17.4827 dB is not satisfying for most target detecting, because there will be serious range ambition if the sidelobe is too high.
During matching filtering, multiplying a window in the frequency domain can suppress the sidelobe to a certain level. But in general, the lower sidelobe is often accompanied by a wider mainlobe after windowed matched filtering.
When K = 0.08 and n = 2, the weighting function is a Hamming window; when K = 0.333 and n = 2, the function is a 3:1 taper weighting, when K = 0 and n = 2, 3, 4, respectively, the functions are cosine square, cosine cube, and cosine quartic weighting.
It can be seen from Figure 10 that the sidelobe is suppressed to the level of –37 dB. From theoretical analysis we can educe that the mainlobe broaden to 1.47 times of the one before windowing.
For Doppler weather radar, to enhance the accuracy of weather target detecting, a lower sidelobe is needed. So, further improvements of pulse compression effects are demanded.
3. Sidelobe suppression by phase predistortion and spectrum modification
For an LFM signal with TB product, the cubic phase predistortion technique can be used to suppress the sidelobe [3, 4]. The signal with little TB product has large ripples in its spectrum band, so widowing is not satisfying for sidelobe suppression. In this situation, the sidelobe suppression can be achieved by suppressing the ripples in band through phase predistortion. This method is easy to implement with surface acoustic wave (SAW) technique.
where ΔT = 1/B and ΔB = 0.75B.
Figure 13 demonstrated that the sidelobes neighboring to the mainlobe are suppressed well (3–4 dB) through matched filtering after phase-predistortion. But in the positions away from the mainlobe, there are some sidelobe hunches and this may bring range ambiguity of two targets far away from each other.
In ideal situation, the output of the matched filter for an LFM signal has rectangular spectrum. After weighting, the rectangular spectrum becomes a certain window. But when the TB product of the LFM signal is small, its ripples in band are large, so the weighting has little effects for ripple suppression in band. In this case, spectrum modification technique can be resorted to make the processed spectrum approaches ideal window function mostly [5, 6] and to enhance the main-to-side lobe ratio.
From Figure 14, it can be seen that spectrum modification technique has good suppression effect for the sidelobes neighboring the mainlobe. What is the most important, this technique bring a great advantage that suppress the sidelobes far away from the mainlobe to the level under –62 dB.
It is stressed that both phase predistortion and spectrum modification did not spread the mainlobe apparently.
4. Combination of phase predistortion and spectrum modification
From Figure 16, it can be seen that
The first sidelobe is suppressed to the level under –45 dB, and the sidelobes attenuate quickly when getting far away from the mainlobe.
The envelope of the sidelobes is monotonically decreasing.
The mainlobe does not spread apparently comparing with the result only using weighting function.
Effectiveness of pulse compression and sidelobe suppression
Mainlobe compression ratio
Sidelobe suppression (dB)
Sidelobe attenuation speed
No sidelobe suppression
Hamming window only
The resolution of weather radar echo is very poor without pulse compression.
Phase predistortion and spectrum modification can bring comparative resolution enhancement through sidelobe suppression. But spectrum modification technique brings some false target echo in the upper left corner of the reflectivity section.
The combination of phase predistortion and spectrum modification has the best resolution.
Furthermore, it is evaluated to statistics the weather echoes SNR of three methods. The mean SNR value of compression with phase predistortion is 0.044 dB less than compression with phase predistortion and spectrum modification, the variance value is 0.4528 dB. The mean SNR value of compression with spectrum modification is 0.017 dB less than compression with phase predistortion and spectrum modification, the variance value is 0.2664 dB.
Figure 18 shows the SNR statistical comparison between phase predistortion method and combined method of phase predistortion and spectrum modification.
Figure 19 shows the SNR statistical comparison between spectrum modification and combined method of phase predistortion and spectrum modification.
Sidelobe suppression is an important part in pulse compression. From the simulations and application on weather radar, it can be seen that the combination of phase predistortion and spectrum modification technique has good sidelobe suppression performance. In some applications involving hardware implementation and real-time processing, the SAW device can be used to carry out impulse compression [7, 8]. Resolution enhancing is important for both weather radar and other kinds of radar, such as the imaging radar [9, 10], so it is still a hotspot for research. The methods development by this article can be used in other kinds of radar with pulse compression systems.
- Lin M, Ke Y: Theory of Radar Signal. Beijing: National Defense Industry Press; 1984:87-203.Google Scholar
- Cook CE, Bernfeld M, Paolillo J, Palmier CA: Matched filtering, pulse compression and waveform design. Microwave. J. 1965, 8: 73-81.Google Scholar
- Cook CE, Paolillo J: A pulse compression predistortion function for efficient sidelobe reduction in a high-power radar. Proc. IEEE 1964, 52: 377-389.View ArticleGoogle Scholar
- Kowatsch M: Suppression of sidelobes in rectangular linear FM pulse compression radar. Proc. IEEE 1982, 70(3):308-309.View ArticleGoogle Scholar
- Lv Y, Xiang J, Chen F: A method for reducing range-sidelobes of linear frequency-modulated pulse compression signals. J. UEST China 1993, 22(4):344-349.Google Scholar
- Yang B, Wu J: A range sidelobe reduction technique based on modifications to signal spectrum. Syst. Eng. Electron. 2000, 22(9):90-93.Google Scholar
- Xianmin Z, Jinlin X, Hongtai W, Qing X: SAW pulse compression systems with lower sidelobes. In Microwave Conference Proceedings, APMC'97, vol. 2. Hongkong; 1997:833-835.Google Scholar
- Arthur JW: Modern SAW-based pulse compression systems for radar applications. I. SAW matched filters. Electron. Commun. Eng. 1995, 7(6):236-246. 10.1049/ecej:19950604View ArticleGoogle Scholar
- Li J, Pi Y, Yang X: Micro-doppler signature feature analysis in Terahertz band. J. Infrared Millim. TE 2010, 31(3):319-328.Google Scholar
- Xu J, Pi Y, Cao Z: Bayesian compressive sensing in synthetic aperture radar imaging. IET Radar Sonar Navigat. 2012, 6(1):2-8.View ArticleGoogle Scholar
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