Low Power LFM Pulse Compression RADAR with Sidelobe suppression

Abstract

ABSTRACT:One of the parameters of the pulsed RADAR that contributes range capability is the average power of the transmitter. The average power can be increased by increasing the peak power or transmitted pulse width or both. The complexity in the design of transmitter components to withstand high peak power is the most challenging task. On the other hand larger transmitted pulse width affects the RADAR capability to detect and track lower range targets. Maximum detection range of RADAR is increased by larger pulse width which in turn results in poor range resolution and poor range measurement accuracy. So narrow pulse width is preferred and therefore only the peak power of the transmitter should be increased. Pulse compression is a technique to enhance the average power of the RADAR without compromising range resolution and maximum detectable range. It is a process of transmitting a longer pulse and on receiving compressing it to a shorter pulse. The emphasis of LFM (Linear Frequency Modulation) pulse compression method combines both the benefits of long duration and short duration pulses to enhance range and range resolution of RADAR without increasing the peak transmit power. But the pulse compression of LFM signal with matched filter introduces sidelobes which is objectionable in a way that they may mask smaller targets in vicinity. The solution to this problem is to introduce windowing technique to suppress the side lobes. A simulation was run to compare various windowing techniques (Hamming, Hanning, Blackman, Flattop, Bartlett) in LFM Signal for effective side lobe suppression in low power RADAR.

New Side Lobe Cancellation Method of Linear Frequency Modulated Radar Signals

“…There are many window techniques used in side lobe elimination or reduction such as Hamming, Hanning, Flattop, and Blackman windowing filter. In [12], it is illustrated that, Hamming windowing has a better performance among the above filter techniques according to resolution and peak of side lobe level.…”

New SAR Algorithm for Sidelobe Reduction in Range direction

“…There are many windowing techniques used in sidelobe elimination or reduction such as Hamming, Hanning, Flattop, and Blackman windowing filters. It has been shown that Hamming windowing has a better performance among other mentioned filter techniques put on the expense of resolution and peak of sidelobe level [5][6][7][8].…”

“…PSLR of LFM MF and OPT filter5. Proposed Sar Algorithm Flow Chart And Simulation ResultsAs shown in figure(5) flow charts (a) Range Doppler algorithm (b) Proposed algorithm using optimum filter. Generation of raw data is done with the block diagram shown in figure (6) of airborne-SAR simulation.…”

Conventional vs. Convolutional Windows for Reduction of Side Lobes

“…The FFT computation takes on the signal as periodic or repeats itself for each block of data. If the signal is non-periodic, it results in the leakage in frequency spectrum of the signal causing the spectrum to spread out over a wide frequency range which arise difficulty in identifying the exact frequency content of the measured signal [7]. So window function is employed to reduce the leakage factor.…”

“…So window function is employed to reduce the leakage factor. When a window function is multiplied to a non periodic signal it makes the signal to be periodic and suppress the side lobes to a certain extent [7]. Window weighting can be applied both in time/frequency domain, the former method is preferred to later as it produces low PSLR values [8].…”