Method for the suppression of disturbances in systems for detecting objects

Translation of description of equivalent WO 03107035 A2

A method for suppressing disturbances in systems for detecting objects

The invention relates to a method for suppressing disturbances in systems for object detection in accordance with the preamble of claim 1st

Systems to detect Objekterfassurig thereby the distance, the relative speed, the relative angle or the image information of objects in the target area. The systems are used, which emit waves and evaluate the echo. Here waves of different physical nature (eg. As sound waves or electromagnetic waves) and different wavelengths come (in electromagnetic waves z. B. in the infrared or

Radar range) is used.

Such systems are used in particular for regulating the distance and speed of vehicles.

Is a wave having the propagation velocity c on an object, for example. A preceding vehicle, reflected in the distance a, so the system receives after the

Duration At = 2a / c, the reflected and i. Gen. Evanescent wave e (t). Thus it can be concluded on the distance of the object from the running time .DELTA.t, as long as the duration .DELTA.t always smaller than the pulse repetition time T_PW(N); in another case arising ambiguity - one speaks of overreach. be captured by the wave object moves with respect. of the measuring system with the relative speed v, so the received from the system reflected wave shows a frequency shift by the Doppler frequency f_D = 2f_sv / c. From the Doppler frequency f_D can thus be closed v to the relative velocity.

Besides overreach there are in practice just in automotive applications is another equally impacting disorder, namely when meet several vehicles with such systems so that pulses of other systems will receive.

In order to suppress such interference, a linear filtering is not, because on the one hand the disturbers only smooths and secondly, the spectral or performance analysis yes i. Allg. representing already a linear filtering minimal bandwidth.

The object of the invention is therefore to provide an improved method for the suppression of such disorders. This object is solved by the features of claim 1.

Advantageous further developments are specified in the dependent claims.

To investigate the influence of overreach and interference, ie mutual interference to reduce pulsed, working in the same frequency range systems to one another, first a pseudo-noise encoding of the pulse repetition T_P (S) used, ie the pulse repetition time is not constant, but is designed a random process to variably.

Received pulses which come from overreach or another pulsed system, then have to immediately previously transmitted pulse is not always the same, but a stochastically distributed distance. However, this measure alone is not sufficient to suppress overreach and interference to a sufficient extent. In overreach and confusion from pulsed, working in the same frequency range systems (with or without pseudo-noise coding) are due to the pseudo noise code of the pulse repetition T_PW(N) in each range i. Allg. only disturbed individual samples - one speaks of transient interferers. But this could be enough in the case of high interference that further signal processing (spectral Doppler to determine z. B. by FFT or performance analysis z. B. by power integration) delivers unusable results.

Bzgl. this problem is a non-linear filtering of the digitized signal (possibly after a corresponding digital preprocessing such as. for example, an absolute value squaring for a power analysis) proposed which specifically eliminates the transient noise. It is in conjunction with this filtering, the special advantage of the pseudo noise code has a particularly because it is the interference power not only distributed stochastically, but due to the now transient disturbances, this proportion is effectively reduced. Preferably, a median filtering process is used, wherein in each case an odd number of successive samples of a detected within a range gate reflection signal of the median is determined. The median filtering is proving to be effective and is also easy to implement. Under the median of an odd number K of values ​​is defined as the average value, ie the (K + 1) / 2-smallest value, or what is the same, the (K + 1) / 2-largest value, i. Other , is different from the average value. For example, results for the five

Values ​​5, 3, 2, 79 and 1, the median 3, as an average value but the value eighteenth

Preferably, a short in relation to the maximum useful frequency median filter is used to reconstruct the superimposed sinusoidal oscillation from the samples without significant attenuation can. Preferably median filter of length between 3 to 9 are used. Particularly advantageous is the use of a multistage median filter has been found in such a short median filtering, in which the median determination repeated so at least twice in succession takes place and thus a better filtering effect is guaranteed with simultaneous low attenuation. Preferably, a sliding median filter is used with overlapping windows of input values, ie, for a given length of the filter compared with the length smaller number of input values ​​considered old is only replaced with new input values. In particular, a sliding median filter with the step 1 can (without decimation of the sampling) are used, that is, compared to the previous Media Education only the oldest input value replaced by the current input value. Thus, the resolution is fully preserved. A two-stage median filter, each of length 5 and an increment of 1 turns out for the considered applications as already extremely effective. within each range gate is preferably performed oversampling.

As an alternative to median filtering more filters are suitable, which must be non-linear, just to dampen only transient disturbances. The invention is explained in detail with reference to exemplary embodiments and figures. The figures show:

Fig 1 a). Amplitude or envelope of s (t) of the transmitted wave in the case of rectangular pulses

Fig 1 b). Amplitude or envelope E (t) of the received wave in the case of an object at the distance a, which results in a signal propagation time of .DELTA.t = 2a / c

Figure 1c):.. Disturbed received signal e (t), for example due to overreach or interference from another pulsed, working in the same frequency range system

Fig. 2a): sine wave which numerous high interfering pulses are superimposed in the discrete time domain; in the spectrum of the resulting signal of the spectral peak of the sinusoidal oscillation has disappeared in the noise generated by the noise pulses

Figure 2b). Output by two-stage median filtering with respective filter length K = 5, in which the sine wave almost completely reconstructed in the time domain again and clearly visible in the spectrum thus is

Figure 3 block diagram of a pulse Doppler radar system 4 simplified circuit diagram for explaining the principle of the Doppler method;

5, the signal-time diagrams for the diagram of Figure 4;

6, the transfer function of an ideal and a real optimum filter;

Figure 7 shows the circuit diagram of a first embodiment of a matched filter;

Figure 8 shows the circuit diagram of a second preferred embodiment of a matched filter; 9a algorithm to implement a median filter with a bit serial

Processing for binary data in binary sign loose

FIGURE 9b algorithm to implement a median filter with a bit serial

Processing for binary data in sign-magnitude representation

Fig.θc algorithm for implementing a median filter with a bit serial processing for binary data in single or double-complement representation

10A, B, C respectively to the detail 9a, 9b, 9c

11, the transfer function of an ideal and a real Dezimationstiefpasses;

Figure 12, the impulse response h (n) of a sliding averaging unit and a

Signal flow diagram; Figure 13 is a advantageous embodiment of a Dezimationstiefpasses. In FIGURE 1a) for a pulsed system, the amplitude or envelope of s (t) of the transmitted wave of the frequency f_s for the case of rectangular pulses. The time points at which to start the transmit pulses are hereinafter with t_P(N), the distance between two successive pulses is the pulse repetition time T_PW(N). If this wave is reflected with the propagation velocity c to an object in the distance a, the system receives after maturity At = 2a / c, the reflected and i. Other. evanescent wave s (t); in Figure 1 b), the amplitude or envelope E (t) is the received wave shown. Thus it can be concluded on the distance of the object from the running time .DELTA.t, as long as the duration .DELTA.t always smaller than the pulse repetition time T_PW(N); in another case arising ambiguity - one speaks of overreach. moves from the

Wave detected object with respect. Of the measuring system with the relative velocity v, as shown by the. System received reflected wave, a frequency shift by the Doppler frequency f_D = 2f_sv / c. Thus, from the Doppler frequency f_D are closed v the relative velocity. In Fig.1c) the amplitude or envelope e (t) of the received wave exemplifies

Overreach or interference from another pulsed, working in the same frequency range system shown.

The starting point for the improved process is a pseudo-noise encoding of the pulse repetition T_PW(N), ie the pulse repetition time is not constant, but is designed a random process to variably. Received pulses which come from overreach or another pulsed system, then have to immediately previously transmitted pulse is not always the same, but a stochastically distributed distance.

The received signal e (t) is preferably after appropriate treatment (eg. Mixing to an intermediate frequency or to baseband, the IQ-formation, filtering) sampled. In this case, the sampling are selected so that they transmit pulse to the previous time t_P(N) a delay t_A(M) me {0,1 ..., M -1} own; each time interval t_A(M), m = 0,1, ..., M -1, corresponds to a so-called Entfemungstor. For each of the M eliminator ungstore N (m) are formed samples per cycle as a whole; in what way this is done, whether such. as serial or parallel, is not relevant for future viewing. In overreach and confusion from pulsed, in the same frequency range working

Systems are due to the pseudo-noise coding of the pulse repetition time T_PW(N) in each Entfemungstor i. Allg. only disturbed individual samples - one speaks of transient interferers. But this could be enough in the case of high interference that further signal processing (spectral Doppler to determine z. B. by FFT or performance analysis z. B. by power integration) delivers unusable results. Fig. 2a shows an example in discrete

Time domain, a sine wave, which numerous high interfering pulses are superimposed; in the spectrum of the resulting signal of the spectral peak of the sinusoidal oscillation has disappeared in the noise generated by the noise pulses.

-Here Now comes the median filtering is used. The median filter lengths are preferably to choose, the higher may be the more values ​​disturbed; at a power analysis can be the

Select Media filter lengths up to the number N (m) of samples, in the case of spectral analysis for Doppler determination the median filter lengths (due to the low-pass characteristic of median filters), which oversampling presupposes the largest limited to be detected Doppler frequency.

. Disturbed signal illustrated in Fig 2a for the results after a two-stage median filter with a respective filter length K = 5, the course shown in Fig. 2b; the useful signal, a

Sine wave is reconstructed almost completely back in the time domain and clearly visible in the spectrum thus.

Thus, when combining the pseudo-noise coding of pulse repetition and the median filtering as a suppression suitable transient interferers nonlinear filtering, so you can reduce the influence of overreach and confusion from pulsed, working in the same frequency range systems greatly or entirely eliminated. In addition, first an adequate pre-processing of samples such. B. is preferably in each Entfemungstor provided a value squaring for a power analysis.

The invention will be presented in its use in a radar system, in particular for a passenger motor vehicle.

Modern motor vehicles are increasingly equipped with a radar-based distance control system, in which the distance, the speed and the relative angle of the preceding motor drive tool is determined.

Such a known radar system, for example, developed by the company Bosch FMCW (Frequency Modulated Continuous Wave), in which two physical quantities

Distance and the relative speed of a moving or stationary body, are mapped to a physical variable, the frequency. For this purpose signals are continuously transmitted and received reflected from the moving body signals. From the frequency response of sent and received signal respectively from the frequency difference of these signals can be close to the size desired. A separation of speed and

Removal is possible by evaluating a plurality of signals, so-called chirp, with varying frequency slope. For a single target two chirps would suffice for multi-target situations at least three chirps are needed.

For operating such a radar system, especially an oscillator (VCO) with low phase noise is required, providing linear frequency ramps as possible, which readily is not possible and thus the RF portion of the radar system is very complicated. In traffic situations with many different goals, as is often the case with guard rails and in the downtown area, there are problems in the target detection and separation arise because all destinations are available in an antenna beam in each associated chirp spectrum. An accurate extraction of the different objectives is therefore not or not always satisfactory possible.

To circumvent these problems, the pulse Doppler method offers. In this method, an object is imaged in each case one or more successive range gates. The received signal is sampled suitable. can then be closed at the exact distance from the amplitude ratio of the samples in consecutive distance gates. However, the pulse Doppler system has a low signal-to-noise ratio (S / N) due to reduced average output power. Due to the broadband receiving path has this radar system at a higher Störbarkeit.

In the pulse Doppler method, a complex sample of the received signal to detect the sign of the velocity made. Radar system according to the pulse

Doppler method are characterized in that the speed and the distance represent direct measures. The RF portion can be realized much easier compared to the FMCW system mentioned, as there is a free-running oscillator (VCO) can be used with low demands on its phase and amplitude noise and no frequency ramps have to be generated.

There are evaluated in such a radar system for a measurement cycle a plurality, for example, in 1024, sending pulses per reception antenna. Their spacing is then eg 2.5μs. The distance is also pseudo-noise-coded to avoid overshooting and interference.

When using a large number of transmission pulses a more accurate speed measurement and a high integration gain is possible and, moreover, the noise generated due to the pseudo noise code is small, so that a more optimal signal to noise ratio can be achieved.

Figure 3 shows by means of a block diagram, the inventive pulse-Doppler radar system. The individual elements of this system, in particular the matched filter and the elements of the FPGA will be explained in more detail.

The radar system includes an RF receiver section having a downstream amplifier, band-pass optimum filter and A / D converter. At the output of the A / D converter a complex output signal can be picked up, which is a downstream FPGA fed. The FPGA consists of a digital modulation device, the median filter to pulse interferences and a low-pass decimation filter formed as arranged in series with each other.

The FPGA unit also includes a PN generator. Further, a noise filter is provided, which is arranged upstream of the A / D converter.

The FPGA downstream is a digital signal processor (DSP) comprising means for generating a window function, an FFT means (Fast Fourier Transformation) and a Störlinienkompensator in the present case. Subsequently, the detection threshold is determined on the basis of and a device for setting objectives, which produces a target list supplied. The DSP is connected downstream of a micro-controller unit (MCU), which generates control values ​​for the vehicle from the destination list, in case of need. For this purpose, first, a "tracking" the destination list made and determined a relevant object. The information about is fed to a series regulator, which then produces the desired manipulated variables. The function of the DSP and the MCU can of course also by a single program-controlled unit, for example, a microcomputer, are met.

Hereinafter, will be explained briefly with reference to Figures 4 and 5, the Doppler method. In this Figure 4 uses a simplified diagram of the principle of the Doppler method and Figure 5, the signal-time diagrams for the circuit diagram of FIG. 4 The Doppler method is a complex sample of the received signal is performed in order to detect the sign of the speed. Radar system with the pulse Doppler method are characterized in that the speed and the distance represent direct measures. The RF section can be characterized in comparison to the FMCW system mentioned realize much easier, as there is a free-running oscillator (VCO) can be used with low demands on its phase and amplitude noise and no frequency ramps have to be generated.

A measurement cycle lasts for example. Each 50ms. The measurement result is a target list that is a snapshot of the traffic situation. Each measurement cycle are 5 measuring blocks, namely a Störlinienmessblock, an IF measurement block and three antenna measurement blocks allocated (for each antenna a). Each of these measurement blocks 2,76ms lasts. During this time, for example, 1024 + 64 transmitter pulses are generated, the first 64 transmit pulses serve the settling of the filter and are thus not recovered. After each transmission pulse 40 times is sampled at intervals of 25ns. This ensures that each target is detected in at least one Entfemungstor.

The switches ANT0 to ANT2 one of three antennas is selected. By closing the transmit switch TX 25ns for the signal of the oscillator is applied to the selected antenna and radiated. After this transmission of a rectangular transmitted pulse the receiver switch RX is closed, and the frequency of the oscillator is changed by 200MHz. Thereby, the

Transformed received pulses through the mixer to an intermediate frequency of 200MHz. The Doppler shift of the frequency may be disregarded at this point. The thus resultant real signal m (t) is applied to one designed as a matched filter passive bandpass which has two mutually orthogonal outputs having the same amplitude and thus generates the complex signal k (t), ie, there is an IQ signal is implemented without complex mixture ,

The IQ signal at the output of the bandpass filter is sampled 40 times after each transmitter pulse at intervals of 25ns. The individual sampling instants corresponding to a respective distance range - they therefore called range gates are possessing and extend to a distance of 150m in width 3.75m. Since a rectangular reception of the pulse length is 25 ns smoothed by the band pass filter to a triangular pulse of twice the length, and thus i. Allg. is visible in two successive range gates, the exact distance can be interpolated by evaluating the amplitude ratios of these two range gates.

To determine the relative speed of the targets with respect to the own vehicle and to increase the signal-to-noise ratio, the complex received signals of 1024 successive transmission pulses are evaluated in each range E, without changing the selected antenna A. In the case of equidistant transmit pulses shows image 4 the real and imaginary d, (n, E, A) and d_Q(N, E, A) of the 1024 complex samples d (n, E, A) of a range in which there is a relatively moving target (during the short observation time of 2.56 ms for the 1024 sample, the relative velocity can always as are considered constant); from sample to sample, the phase changes uniformly, since changing the distance of the target and thus the phase of the received pulse uniformly - it results exactly the Doppler frequency including its sign (because the signal is complex).

The method just described is applied sequentially for each of the three antennas. One of the antennas is looking straight ahead, while the other two are slightly tilted to the left or right in order to determine as the position of the detected targets relative to the own lane can.

The received signal always includes a noise amount, which manifests itself as noise. The disorder has approximated to the characteristics of white noise. To this noise as well as possible to filter out, ie a maximum signal-to-noise

to obtain money, a matched filter is used. Its transfer function corresponds to the spectrum of the received intermediate-frequency pulses (pulses IF), i.e., the spectrum of a modulated with the pulse width 25ns 200MHz rectangle. The optimum filter thus corresponds to a bandpass. The matched filter used is advantageously used as an embedded in ohmic resistances

LC quadrupole realized. In the frequency range this is a particularly convenient and flexible technology, as required for this purpose inductors are available as SMD components. The filter circuit can thus very simple, small and thus also inexpensive to build.

In the design of such a matched filter according to the known method according to Bader two design strategies are possible:

1. First, a required pursuant matched lowpass is designed. a transformation of the low-pass filter is then made it into a bandpass. This variant, however, is of limited use, and only for special circuits, since it leads to the realization of the circuit unsuitable structures and components values. 2. Direct design a bandpass filter: This variant is particularly advantageous, although somewhat more expensive and the design because it leads to different alternative structures that are more or less well adapted, depending on demands on the required conditions. In this method, an approximation of the ideal transfer function is performed. Fig. Figure 6 shows in phantom the transfer function of a direct draft produced in

Matched filter; the thin continuous curve belongs to the ideal matched filter, which is very well approximated or simulated by the real circuit.

7 shows a first circuit arrangement for the realization of an approximated by Bader matched filter: The values ​​of inductors, capacitors and resistors are rounded to real disposable values. Degrees of freedom in development were here so exploited that advantageously no transformer is needed. The structure shown in Figure 7, in contrast to its dual structure of almost every node capacitances to ground, in which the stray capacitances can be included in the calculation. The output signals k | (t) and ko (t) of the circuit in Figure 7 are orthogonal to each other, ie, they have a phase difference of 90 ° to one another, and possess at the intermediate frequency fIF = 200MHz same amplitude, which is achievable through degrees of freedom in development ,

The complex output signal k | (t) + j * ko (t), hereinafter referred to as IQ signal, thereby constitutes a complex oscillation of the real input vibration having the intermediate frequency fIF.

This so-called IQ signal was realized advantageously without any mixture.

It is particularly advantageous if both of the real part and the imaginary part associated with the output signal, so kι (t) and k Q (t), are designed to ground. 6 shows using a circuit diagram a second, preferred embodiment of an approximated optimum filter in which this account receivable is worn. The output side of the

Filter circuit was thereby doubled substantially.

This illustrated in Figure modified output stage has the further advantage that despite resistive and capacitive load of the A / D converter of the I / Q character of the output signal is maintained. Only the filter characteristic changes slightly. A according to the Figures 7 and 8 formed band-pass optimum filter thus comprises in summary the following advantageous functions:

The filter has an optimized signal-to-noise ratio.

The filter produces a largely accurate IQ signal can be picked off at the output of the filter in a simple, but very reliable way. - Since the triangular output signal is visible in two range gates and over the

Amplitude ratio, the distance can be determined, a simple interpolation of the distance is possible in this way.

The FPGA block in Figure 3 has a device for digital modulation generated by the matched filter complex output signal. Such a device is necessary because the velocity range of interest is not symmetrical and typically would lead to an unbalanced frequency range; in Application Example interest rates in the range of -88.2 to +264.7 km / h. By means of a frequency offset of -12.5kHz can it create a symmetric frequency range. By means of an appropriately dimensioned device for digital modulation can be realized that, for example, by multiplication of the sampled IQ-signal with a signal which is generated by a rotating complex phasor amplitude of 1 and the rotational frequency -12.5kHz.

Further, the FPGA block comprises a nonlinear filter against pulse interferences. Pulse-shaped disturbances originate eg overreach or pulse radar systems of other traffic participants. A pseudo-noise coding of the sampling pulse interferences are all distance gates (more or less uniformly) distributed. This only individual values ​​are disturbed in each range. By pseudo-noise coding and non-linear filtering, for example, by Media Filter, unwanted pulse interferences can be compensated.

For the realization of the filter against pulse interferences following issues should be considered: A linear filter is here less advantageous because of the filter subsequent Dezimationstiefpass already represents a linear filter with minimal bandwidth. Conceivable are all non-linear filters, which can compensate for individual Fehiwerte; many of these filters, however, are problematic in terms of stability and implementation on a FPGA. Here is advantageously to use a single- or multistage median filter. In a preferred embodiment, this filter has two stages, each with the length 5. Advantageously, by the upstream A / D converter oversampling performed.

The median of K values ​​is the middle value, ie the (K + 1) / 2 = smallest value (K + 1) / 2-largest value. For example, the median of the five numbers 5, 3, 2, 79, 1 is equal to 3. A sliding median filter without reduction of the sampling rate calculated at each instant n the median of K successive values ​​of an input sequence x (n) and generates an output signal m (n). For median filter many algorithms are known which are particularly suitable for a software implementation. These are based on sorting with concomitant high computation time or statistical analysis with concomitant high memory requirements of data. For a

Hardware implementation of these algorithms are not very suitable, because they typically require too many case distinctions and branches.

However, a new algorithm for a hardware realization of a median filter, it has now been developed: The operation is shown 10a, 10b, 10c below with reference to figures 9a, 9b, 9c and.

They show an algorithm for implementing a bit-serial processing to determine the median. With such a structure can be significantly reduced in many cases the cost of a median filter, especially if the maximum cycle time of the FPGA is substantially greater than the word clock of the input signal. A further advantage consists in the easy scalability of the structure.

In the figures 9a, 9b, 9c and 10A, 10b and 10c variants of the filter algorithm for the median calculation in the form of a one-dimensional filter are shown without decimation, wherein the 9a in connection with the construction of Figure 10A for input values ​​in unsigned binary notation show, while FIGURE 9b in conjunction with the modification 10B for a sign magnitude representation of the input values ​​and the 9C in connection with the Fig.10c

Modification of a single or double-complement representation of the input values ​​illustrate. To explain the following points are noted:

The input signal x (n) and the output signal consisting of the medians m (n) have the word length W, which is any value consists of W bits. The individual bits are numbered v, starting at v = 0 for the MSB (in unsigned binary in 9a, 10a and digit and twos in 9C, 10c) or the VZB (in of sign magnitude representation in FIGURE 9b, 10b) and ending at V = W-1 for the LSB. The bit is denoted by x (n, v) and m (n, v) v x (n) or M (n).

The time at the level of input and output signals, ie word level is denoted by n, time at the bit level with μ = nW + v. The processing is bit-serially, ie one bit after another is processed, beginning with the MSB or VZB and ending at the LSB. The entire filter structure, ie memory and logic, ie clocked μ with the bit time.

The input values ​​required for calculating Media bitwise using K consecutive shift registers of length W; while K is the median filter length.

The flag B0 (μ) denotes the processing of bit 0; it is 1 for v = 0, and otherwise 0. The flags B1 (μ) and LSB (μ) denote the processing from the bit 1 and the LSB; they are defined in a similar way and can be generated by delay of B0 (μ) to a or W-1 clocks. In the block "median of K bits" bitwise Media education takes place, ie the majority of zeros or ones among the K fed bits is determined.

In the k-th block "to be used bit value" (k = 0,1, ..., K-1 is viewed from above), which is in detail in each case. Figures 10a, 10b and 10c, on the one hand the kth bit value w (nk, v) determined for the bit Media education: this is either the original value x (nk, v), ie the input value x (nk) bit looked v, or an appropriately modified value. Secondly, it is determined whether the next bit clock μ + 1 of the original value or an appropriately modified value is to use what is already by the flag ok (μ) = 1 for the previously performed modification or ok (μ) = 0 for performed modification is marked. The following from the procedure described above is generally considered that after the first use of a modified value of this to be used also below n to the end of each time step. Subsequently, ie LSB (μ) = 1, the flag is reset, ie the unmodified input value is initially for the next baseline again considered.

The initialization of the memory (shift register and retarder) depends on the desired On stopping behavior of the filter. In following this new median filter structure should respect. Its expenses at a hardware

Realization (. Eg on an ASIC or FPGA) be considered:

Bitwise Media Education, ie the determination of the majority of zeros or ones among the K bits fed, is the central block of this structure. One possible, particularly suitable for large filter lengths K strategy for realizing this block is based on the summation of the bit values ​​(0 or 1). If the bit sum> = (K + 1) / 2, as is the Bitmedian equal to 1, otherwise

0; the comparison can be implemented via a subtraction and subsequent testing of the sign. The Bitsummenbildung can for example be realized in parallel stepped shape in which, step by step, the number of parallel Einzeladdierer off and their word length increases. thereby patting one hand the critical path and thus the processing time required to minimize and on the other hand hold the required word length and thus the expenditure as small as possible. The minimization of the critical path is particularly important when a high cycle life of the filter gefo is promoted, since the bit-wise median formation lies in a recursive loop and therefore secretes a pipelining. For small filter lengths there is the realization of the bitwise Media Education special, optimized for the used hardware solutions. Considered as an example, the filter length K = 5 and the implementation on a FPGA market, which the basic building block look-up tables (LUTs) with four logical inputs and one output logic possesses; there are then three such LUTs for bitwise Media education needs.

The K identical blocks "bit value to be used" need only two retarder (FIFOs) and a very simple logic (in the above example 2 LUTs). The K shift register for storing the input values ​​need in many cases

(Especially when the word length W is relatively large) much more effort than the rest of the filter structure, which speaks for the efficiency of the filter logic. It should be noted that a storage independent of the structure of K input values ​​in each median filter is necessary.

The new median filter structure is scalable, if the bit median determination is realized via a summation; when changing the filter length K only the number are used

Shift register, the number of identical blocks "to be used bit value" and the number of bits be summed up and the bit sum adapt the value to be compared.

The new median filter structure has the property that the media education for each input value, ie each time step n, brand new touches, so unlike most existing structures does not rely on the results of previous time steps; For example, in

Sorting method i. Alig. starting from the determined in the previous cycle sequence. Because of this characteristic, the new algorithm for median calculation is especially the case for filtering with decimation. Therefore only the shift register shall be supplied in a modified form in the filter structure. Thus, for a decimation by a factor of L = 2, the two uppermost shift register to be fed in parallel to two successive input values, and wherein the coupling of the shift register in each case one is skipped. In a decimation by the median filter length, ie L = K, the shift registers are no longer coupled, but are fed in parallel with K successive input values. By decimation of the maximum processable by the filter structure clock rate of the input signal x (n) can be increased by the decimation L.

For hardware implementations of the digital filter, the new algorithm for median calculation in many cases leads to a considerable reduction of the effort required; This is mainly dependent on the clock rate and the word length of the input signal, the degree of decimation, and the technology used or available logic. The FPGA block in Figure 3 further includes a decimation. The decimation filter is advantageously designed as low-pass.

In the present embodiment, a decimation of the sampling frequency of 400kHz to 50 kHz, that is by a factor of 8, made. Characterized - in the case of an ideal Dezimationstiefpasses - an improvement of the signal-to-noise ratio by up to 9dB possible.

A real Dezimationstiefpass must fulfill the requirements steepest possible flanks to the frequencies f = ± 25kHz around. It is not necessary | Hreal (j2πf) | ~ Const in

Passband I f I <25kHz, as in the evaluation only spectra to be recycled and thereby can be easily compensated for amplitude error. In Figure 11, the transfer function of an ideal and a real Dezimationstiefpasses shown. The for Lowpass used consists of two moving average formers, the second is already working with the halved input clock rate. The moving averaging of length N averaged over the current and the N-1 preceding values. Figure 12 shows the impulse response h (n) of such a sliding averaging unit and a signal flow diagram. The averaging can be implemented very efficiently in recursive form.

The overall structure of an advantageous embodiment of a Dezimationstiefpasses is shown in FIG. 13 A missing factor 64/40 at the output is at a subsequent windowing for digital Fourier transform (DFT) with realized. For such a decimation filter with the level 15 so the following elements must be provided: a shifter, four adders, four storage elements. However, a multiplier is not required, in comparison with a conventional linear-phase filter having a total of eight degrees 15 multiplier, 15 adder, 15 memory must be provided. The decimation is thus characterized by a significantly lower outlay on circuitry.

In the above example, a median filter for suppression was used transient disturbances. Below are alternative nonlinear digital filtering methods are presented.

Thus an estimate of, for example, successively for each sample from the preceding it samples by extrapolation determine the sample considered is compared to its estimated value and recognized disturbed with a deviation of the observed sample of its estimated value by more than a predetermined threshold, this sample as a transient and replaced by his estimate.

If, as produces a complex signal having an I component and a Q component in the previously described application, from the received reflection signal may, alternatively, determines the power in each case also a sample from the I and Q fraction and with a over several previous comparing samples averaged power value and disrupted in deviation of the power above a predetermined threshold value of the current sample as transient identified and replaced with an extrapolated value from the previous samples.