Patent GB-1319740-A (GB)
Title: Detecting radar signals in the presence of coloured noise
IPC: G01S7/292
Filed: 1971-10-28
Abstract: 1319740 Adaptive whitening filter for a pulsed radar INTERNATIONAL STANDARD ELECTRIC CORP 28 Oct 1971 [30 Oct 1970] 50075/71 Heading H4D In a pulsed radar a matched filter arrangement for detecting return signals in the presence of coloured noise is characterized in that it includes an adaptive whitening filter which transforms received signals in such a way that the noise component of the resulting transformed signals is white. The Specification observes that prior art arrangements have assumed that the noise component in return signals has had known fixed characteristicsusually white-but that in practice the characteristics of noise vary with time. White noise has the property that if it is repeatedly sampled, each sample is statistically independent of each other. Ideally, according to the specification, return signals, which are almost entirely noise, would be repeatedly sampled, the statistical characteristics of the noise would be computed after every sample using the preceding n samples, and a transformation (i.e. an appropriate circuit) would be calculated which when applied to the return signal would produce white noise. However, such a calculation is impracticable in the time available. The arrangement described therefore approximates to such a solution by progressively modifying return signals in such a way that after each modification the degree of coloration of the noise is reduced. This is achieved in the following manner. The received signal over a range cell is repeatedly sampled to provide signals y 1 , y 2 , ..., y n , which are referred to collectively as the components of a vector y. In general with coloured noise correlation will exist between each of these component signals. Once this correlation is removed the noise is white (assuming that the noise is also Gaussian, which is the only practicable assumption possible), and it is removed, or at least substantially reduced, by the repeated use of a plurality of adaptive filter elements referenced A in Fig. 4, each of which in response to two input signals, which may be correlated, produces two output signals which are uncorrelated. The sampled signals y 1 , y 2 , ..., y n  are applied in pairs to a first column T 1  of adaptive elements A. This removes any correlation between non-overlapping adjacent pairs. The resulting n signals are applied in pairs in a different order to a second column T 2  of adaptive elements, thereby further reducing any correlation present, and this process is repeated. According to the Specification c columns of adaptive elements A will satisfactorily whiten 2<SP>c</SP>-component sampled signals. In the preferred embodiment, Fig. 1, return signals y(t) are sampled 1 over a range cell to produce a block of n signals y(t) which are whitened by a filter 2 comprising an array of adaptive elements as shown in Fig. 4, and a replica S of the transmitted signal is also subjected to the same transformation by a filter 3 slaved to filter 2. Corresponding component signals from each of the two whitened signals Wy and Ws are multiplied together and summed and applied to a threshold circuit, so that a decision as to whether the received signal y contains S can be made in the way that is conventional for matched filters. However to take into account the fact that the replica signal has been transformed by W, the threshold detector also has to receive the sum of the squares of the component signals of the whitened signal Ws. The Specification outlines the construction of the adaptive elements A. Each comprises a unit 17, Fig. 3, which produces signals equal to the sum and difference of two input signals (Fig. 3a, not shown) and two automatic gain control elements 20, 21, each comprising conventional retroactive loops (Fig. 2, not shown) whose gains are such that the final output signals 22, 23 have unit variance (i.e., the time integral of their squares over an appropriate period equals unity). It can easily be seen that whatever covariance existed between the input signals it is completely removed from the normalized output signals.