Techniques to design sub-arrays for radar antennas

Aspects of the Subarrayed Array Processing for the Phased Array Radar

“…The pattern control approaches include normalization method, MOD (mismatched optimum detector), and SSP (subspace projection). Therein, the starting point of the normalization method [2,25,29,30] is the amplitude taper combined with the different number of elements for each subarray, which implies the receiver noise level is different at the subarray output. The subarrayed ABF tries to find a weight giving equal noise power in all subarrays and cancels the low sidelobe taper; that is, the adapted weight tends to be the vector with uniform tapering.…”

“…The scheme generates sum and difference channels simultaneously only using an analog weighting. In order to determine the analog weights, it is assumed that the supposed interferences locate within the sidelobe area of sum and difference beams [25]. Then the supposed interferences are adaptively suppressed (e.g., based on LCMV criterion).…”

“…Similarly, Farina with different coauthors has given creative and pioneering contributions to the following aspects, including subarrayed weighting for SLC [25,26], subarrayed adaptation and superresolution [25][26][27], and subarray optimization [25,28]. Lombardo and his co-authors contributed great achievements to subarrayed adaptive processing and pattern control [29,30], SASP for thinned arrays [31,32], while Massa et al contributed in the fields of subarrayed weighting, synthesis of sum and difference patterns for monopulse [33][34][35][36]; Liao et al in the field of subarrayed 2 International Journal of Antennas and Propagation ABF, subarrayed STAP and subarray architectures [23,37,38]; Wang et al in the field of subarrayed STAP and subarray configuration [39][40][41][42]; Klemm in the field of the design of the subarray configuration for STAP [43], and so forth.…”

Advanced optimization for subarray structure in electronic warfare environment

“…Recently, subarray level ADBF has been studied intensively [1][2][3] , and the genetic algorithm could be used to gain a better jammer suppression performance. whereas most are out of considering the subarray structure that leads to the huge amount of cost for hardware.…”

Sidelobe suppression approach at subarray level for sum and difference beam without analog weighting

“…In addition, it can acquire and accumulate involved information of search space automatically and control search process adaptively to achieve optimum solution. Because of its excellent performance of enlarging search area and keeping optimization efficiency at the same time, GA is applied widely in subarray partition matter for phased array radar [2][3][4] .…”