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This paper proposes an estimation technique for multiple constant amplitude chirp signals embedded in white Gaussian noise. It is shown that it is possible to estimate the parameters (initial frequencies, frequency rates, direction of arrivals) of individual signals with 1-D searches, yet performs close to Cramer Rao bound. Hence it is computationally attractive. The proposed algorithm uses multicomponent discrete polynomial phase transform at each antenna output to observe each initial frequency and frequency rate, and exploits the linear relationship of initial frequency seen at one sensor to the next, to extract the original parameters. Simulation and comparative results are included to show its effectiveness.